SCHOOL OF ENGINEERING & BUILT ENVIRONMENT

Size: px
Start display at page:

Download "SCHOOL OF ENGINEERING & BUILT ENVIRONMENT"

Transcription

1 SCHOOL OF ENGINEERING & BUIL ENVIRONMEN MARICES FOR ENGINEERING Dr Clum Mcdonld

2 Contents Introduction Definitions Wht is mtri? Rows nd columns of mtri Order of mtri Element of mtri Equlity of mtrices Opertions with mtrices Mtri ddition Mtri sutrction Sclr multipliction of mtri Mtri multipliction Mtri multipliction nd the sclr (dot) product Specil mtrices rnspose mtri Properties of trnspose mtrices he identity mtri he zero mtri Digonl mtrices Upper nd lower tringulr mtrices Symmetric mtrices he determinnt nd inverse of mtri Properties of inverse mtrices he determinnt nd inverse of μ mtri he determinnt μ mtri Determinnts nd the Rule of Srrus he inverse of μ mtri y the cofctor method 7 Eigenvlues nd eigenvectors of mtri 7 Clcultion of eigenvlues 7 Rel distinct eigenvlues 7 Repeted eigenvlues 7 Zero eigenvlues 7 Comple eigenvlues of rel mtrices 7 Clcultion of eigenvectors 7 Some properties of eigenvlues nd eigenvectors Eercises & Answers

3 Mtrices Introduction his unit introduces the theory nd ppliction of mthemticl structures known s mtrices With the dvent of computers mtrices hve ecome widely used in the mthemticl modelling of prcticl rel-world prolems in computing, engineering nd usiness where, for emple, there is need to nlyse lrge dt sets Emples of the pplictions of mtrices occur: in ll res of science to solve (lrge) systems of equtions in computer grphics to project three dimensionl imges onto two dimensionl screens nd pply trnsformtions to rotte nd move these screen ojects in cryptogrphy to encode messges, computer files, PIN numers, etc in usiness to formulte nd solve liner progrmming prolems to optimise resources suject to set of constrints Definitions Before we undertke clcultions involving mtrices it is firstly necessry to present some definitions nd terminology Wht is mtri? A mtri is n ordered rectngulr rry of numers nd/or vriles rrnged in rows nd columns nd enclosed in rckets For our purposes these elements will tke the form of rel numers In generl, mtrices re denoted y upper cse letters Emple he following re ll mtrices: (i) A (ii) B (iii) 8 K (iv) M 8

4 Rows nd columns of mtri A useful interprettion of the structure of mtri is to consider the rows nd columns of the mtri hese re simple nd ovious concepts; ut we need to know tht the rows re numered strting from the top (ie Row ) nd the columns re numered strting from the left hnd side of the mtri (ie Column ) For emple we hve, Row Column Order of mtri he size, lso clled the order or dimension, of mtri is identified y numer pir in the form m n, where m is the numer of rows in the mtri nd n the numer of columns A m m n n mn We sy tht the mtri A is m y n mtri A mtri with the sme numer of rows s columns, ie m n, is clled squre mtri Emple he mtrices in Emple hve the following sizes: (i) A is mtri, ie rows nd columns (ii) B is mtri, ie rows nd columns (iii) K is mtri, ie rows nd columns (iv) M is mtri, ie rows nd column

5 Element of mtri Ech element, or entry, in mtri is denoted y lower cse letter, with pproprite suscripts, indicting its row nd column position Hence, element i j is locted in the i-th row nd j-th column of the mtri A s shown elow: A m m n n mn Emple For the mtri 8 A, 7 9 (i) element, s it is locted t Row, Column (ii) element, s it is locted t Row, Column We cn esily drw prllels etween mtrices nd computer rrys s used in progrmming lnguges For emple, in C if A is n rry we would use the synt A[][ ] to inde the element in the second row nd third column of A, in Mple we would use the nottion A[, ] nd in MALAB we would write A(, ) Equlity of mtrices wo mtrices A nd B re equl if nd only if: they re of the sme size, ie oth re m n mtrices their corresponding elements re the sme, ie i j i j for i,, m nd j,, n

6 Emple Determine the vlues of w,, y nd z tht gurntee the mtrices A nd B re equl, y A, B z 7 w Solution We require w,, y, z 7 z Opertions with mtrices We now look t some sic rithmetic opertions with mtrices Mtri ddition wo mtrices cn e dded if nd only if they re of the sme size o dd two mtrices we dd corresponding elements he result of the ddition is mtri of the sme size Mtri ddition is commuttive, ie A B B A, see prts (ii) nd (iii) in the following emple Emple In ech of the following crry out the specified ddition (i) , 7 (ii) (iii)

7 Mtri sutrction wo mtrices A nd B cn e sutrcted if nd only if they re of the sme size o form B A sutrct ech element of B from the corresponding element of A he result of the sutrction is mtri of the sme size As for sutrction of rel numers, mtri sutrction is not commuttive, ie A B B A, see the net emple Emple In ech of the following crry out the specified sutrction (i) 7 8 (ii) 7 8 Sclr multipliction of mtri Any mtri cn e multiplied y numer (sclr) nd this procedure is referred to s sclr multipliction Sclr multipliction is performed y multiplying ech element in the mtri y the numer Sclr multipliction must not e confused with mtri multipliction which will e defined lter Emple 7 Simplify ech of the following y performing the sclr multipliction (i) 8, (ii)

8 7 Emple 8 Let, B A nd 9 C If possile simplify ech of the following: (i) B A, (ii) A B (iii) A C Solution (i) B A 8 7 (ii) A B 8 (iii) We re unle to clculte A C s the mtrices hve different sizes Here C is mtri while A is mtri

9 Mtri multipliction Mtri multipliction cn only e crried out etween mtrices which re conformle for mtri multipliction wo mtrices A nd B, with sizes m n nd p q respectively, re conformle for multipliction if nd only if n p ; ie the numer of columns of A is the sme s the numer of rows of B he result of multiplying m n mtri, A, nd n p q mtri, B, where n p, is m q mtri nd we write the product s AB Note tht mtri multipliction my e defined for A B ut not necessrily for B A Hence, mtri multipliction is not in generl commuttive Note: If the inner dimensions n nd p re equl we cn multiply the mtrices nd the resulting product mtri hs size given y the outer dimensions, ie m q A B Result AB ( m n) ( p q) ( m q) n p If required further resources on multipliction of mtrices topic cn e found t: 8

10 Emple 9 Determine which of the following mtrices re conformle for mtri multipliction A, B, C Solution he mtri A is he mtri B is he mtri C is (i) First consider the mtri product, A B A B ( ) ( ) Not equl he inner dimensions re not equl nd so we cnnot perform the mtri multipliction he numer of columns in A () does not equl the numer of rows in B ( ) (ii) Now consider the mtri product, A C A C ( ) ( ) Equl he inner dimensions re equl nd so we cn perform the mtri multipliction nd the product mtri will hve size given y the outer dimensions, ie Eercise Confirm the following: BA, AC, CB nd BB re vlid multiplictions; wheres we cnnot clculte the products AB, BC, AA or CC 9

11 Mtri multipliction nd the sclr (dot) product o multiply two mtrices, conformle for mtri multipliction, involves n etension of the dot (sclr) product procedure from vector lger o form the result of multiplying A (on the left) y B (on the right) ( ie to form the product AB ) we view A s mtri composed of rows nd B s mtri mde up of columns he entries in the product mtri re determined y forming dot products o determine the element in Row i / Column j, ie position ( i, j ), of AB we form the dot product of Row i of mtri A with Column j of mtri B Emple Let A nd B he product mtri AB cn e clculted s A hs size nd B hs size, ie the numer of columns of A is the sme s the numer of rows of B he product mtri, AB will hve size For emple, to otin the element in Row /Column, ie position (, ) of AB we tke the dot product of Row of A with Column of B, ie

12 o otin the element in Row /Column, ie position (, ) of AB, we tke the dot product of Row of A with Column of B In vector form we hve, ) ( ) ( ) ( his process cn e continued to generte the components of the product mtri, AB ) ( ) ( ) ( ) ( ) ( ) ( ) ( Emple Let A nd B If possile clculte AB nd BA Solution In this cse A nd B re oth (squre) mtrices nd so we cn clculte AB nd BA he result of oth multiplictions will e mtri We hve ) (

13 8 B A nd 9 A B Note: his is n emple of very importnt result in mtri rithmetic In generl, for squre mtrices A nd B, we hve tht BA AB Emple If possile evlute the following mtri products: (i), (ii), (iii) y (iv) ( ) (v) ( ) Solution (i) he product cn e formed s the first mtri hs size nd the second mtri hs size, ie the numer of columns in the first mtri () is the sme s the numer of rows () in the second mtri he product mtri will hve size Multipliction gives, ) ( ) ( ) ( ) ( ) (

14 (ii) ( Eercise: Check this nswer ) (iii) y y ( Eercise: Check this nswer ) (iv) ( ) he product cn e formed s the first mtri hs size nd the second mtri hs size, ie the numer of columns in the first mtri () is the sme s the numer of rows () in the second mtri he product mtri will hve size Multipliction gives, ) ( ) ( ) ( 8 (v) ( ) he product cnnot e formed s the first mtri hs size nd the second mtri hs size, ie the numer of columns in the first mtri () is not the sme s the numer of rows () in the second mtri

15 Emple Let 8 A nd 9 B Clculte the mtri products AB nd BA Solution (i) AB, BA Eercise: Verify these clcultions Unlike Emple we find tht in this cse mtri multipliction is commuttive nd BA AB his prticulr squre mtri, with s on the min digonl (top left to ottom right) nd s everywhere else, is known s the identity mtri see Section for further discussions Emple Determine the vlues of nd y tht stisfy the following mtri eqution y Solution Epnding the left-hnd-side (LHS) gives, y y y A We therefore hve three equtions he first two of these re oth equtions in one vrile which cn esily e solved for nd y he third eqution cn e used to check our nswers, y y y

16 Specil mtrices here re severl specil mtrices tht we should e wre of s they will e needed in future clcultions rnspose mtri he mtri otined from mtri A y interchnging the rows nd the columns of A is clled the trnspose of A nd is denoted A We refer to this mtri s, A trnspose Emple Let A 7 Write down the mtri A Solution he mtri A is otined y interchnging rows nd columns of the mtri A Hence, A 7 Note tht Row of A is Column of Alterntively, Column of A is Row of A nd Row of A is Column of A, etc A Properties of trnspose mtrices ( A ) A the trnspose of trnspose mtri equls the originl mtri ( AB ) B A the trnspose of mtri product equls the product of the trnspose mtrices, with the order of multipliction reversed ( A B) A B the trnspose of mtri sum equls the sum of the trnspose mtrices ( k A ) k A the trnspose of mtri multiplied y sclr equls the sclr multiplied y the trnspose of the mtri, k is sclr

17 he identity mtri We know tht when ny numer is multiplied y the numer the vlue of the originl numer is unchnged, eg 9 9,, etc In this contet we cll the identity element for multipliction We now define n identity element for mtri multipliction so tht when mtri is multiplied y the identity it remins unchnged his identity element is clled n identity mtri nd is only defined for squre mtrices Although there is only single multiplictive identity, ie, when working with numers there re mny different identity mtrices depending on the size of the mtri in question, eg,, etc he identity mtri hs s on the min digonl ( the digonl strting t top left nd going to ottom right ) nd zeros everywhere else see Emple he mtri is usully represented y the letter I Note tht some tetooks include suscript n, nd write I n, to indicte the size of the identity mtri Emple (i) he identity mtri is, I (ii) We met the identity mtri, I in Emple he zero mtri he zero mtri is mtri for which every element is zero Strictly speking there re mny zero mtrices, one for ech possile size of mtri Here re the nd zero mtrices he zero mtri is the identity mtri for mtri ddition

18 7 Emple 7 If 9 A then 9 9 he mtri A is unchnged y ddition of the zero mtri Digonl mtrices A squre mtri is clled digonl mtri if ll the entries tht do not lie on the min digonl re zero Note tht it is llowed for some entries on the min digonl to equl zero Emple 8 he following mtrices re ll emples of digonl mtrices: (i), (ii), (iii) he identity mtri is specil cse of digonl mtri where ll the digonl entries re equl to Upper nd lower tringulr mtrices An upper tringulr mtri is squre mtri in which ll the entries elow the min digonl re zeros Note tht some entries on the min digonl nd/or ove the min digonl cn equl zero Emple 9 he mtrices elow re ll emples of upper tringulr mtrices (i), (ii) 9, (iii)

19 8 A lower tringulr mtri is squre mtri in which ll the entries ove the min digonl re zeros Note tht some entries on the min digonl nd/or elow the min digonl cn equl zero Emple he mtrices elow re ll emples of lower tringulr mtrices (i), (ii) 9, (iii) Symmetric mtrices A squre mtri is clled symmetric mtri if it is equl to its own trnspose, ie A A Emple he following mtrices re ll symmetric (i) (ii) (iii) 9 You re now redy to ttempt the multiple choice eercise t the link elow In the net section we look t how to clculte the determinnt nd inverse ( if it eists ) of mtri

20 he determinnt nd inverse of mtri Consider the following rithmetic evlutions for numers, One wy of interpreting the ove is tht ny (non-zero) numer hs ssocited with it multiplictive inverse Furthermore, ny numer multiplied y its inverse equls, the multiplictive identity for sclrs We cn mke n nlogous sttement for (some) squre mtrices tht will prove useful lter For generl mtri, A provided c d det ( A ) d c, there eists nother mtri, clled the inverse of A, denoted A, where A d det ( A) c he quntity det ( A ) is clled the determinnt of A nd is often written, A he determinnt of mtri cn therefore e used to determine the eistence (or otherwise) of mtri inverse y checking tht it is non-zero In mnner similr to tht oserved erlier for sclrs, A A A A I 9

21 where I is the identity mtri with the sme size s the squre mtri A Also, A I I A A Note tht A must not e interpreted s, A A mtri with n inverse is clled invertile or non-singulr A mtri with no inverse is sid to e non-invertile or singulr We now look t how to determine inverse mtrices, where they eist, for the cse Emple Clculte the determinnt of ech of the following mtrices Hence, identify which mtrices re invertile nd for ech invertile mtri clculte its inverse (i) 7 A (ii) B (iii) C (iv) M Solution (i) det ( A ) ( ) ( ) No inverse (ii) det ( B ) 7 7 Mtri hs n inverse B Eercise: Check tht B B B B I 7 7 (iii) det ( C ) No inverse

22 (iv) det ( M ) ( ) ( ) Mtri hs n inverse, M Eercise: Check tht M M M M I Properties of inverse mtrices If A nd B re invertile mtrices: ( A ) A the inverse of n inverse mtri equls the originl mtri ( AB ) B A the inverse of mtri product equls the product of the inverse mtrices, with the order of multipliction reversed ( k A ) A the inverse of mtri multiplied y sclr equls the k inverse of the sclr multiplied y the inverse of the mtri, k is sclr ( A ) ( A ) the inverse of trnspose mtri equls the trnspose of the inverse mtri Aside: Geometriclly, the solute vlue of the determinnt of mtri A is c d the re of prllelogrm whose edges re the vectors (, ) nd ( c, d ) y O

23 In the net section we look t how to clculte the determinnt nd inverse of mtri he determinnt nd inverse of mtri here re numer of techniques ville for clculting the inverse of mtri In our work we shll focus on the cofctor method Before looking t finding the inverse of mtri, when it eists, we need to know how to clculte the determinnt of mtri he determinnt mtri Define mtri A o clculte the determinnt of A we cn epnd y ny row, or y ny column of A, nd we will otin the sme vlue for det ( A ) Epnding y Row : det ( A ) Note the minus sign on the centrl term, which is eplined elow We cn now evlute the determinnt, det ( A ), s we lredy know how to clculte determinnts Epnding y Row : det ( A) Epnding y Row : det ( A ) In the three cses descried ove note the rry of signs tht prefi the coefficients i j, ie In similr mnner we cn epnd on ny of the columns of A using the sign rry ove

24 Epnding y Column : det ( A ) Epnding y Column : det ( A) Epnding y Column : det ( A ) Note: he vlue of the determinnt will lwys e the sme regrdless of which row or column we perform the epnsion on Emple Clculte the determinnt of the mtri, A Solution Epnding on the first row gives: det ( A ) ( 9 8 ) ( 9 7 ) ( 8 7 ) 9

25 Emple Clculte the determinnt of the mtri, M Solution: Epnding on the first row gives: det ( M ) ( ) ( ) ( ) As we sw erlier the vlue of the determinnt of squre mtri cn e used to determine if mtri is invertile If the determinnt is non-zero the mtri is invertile, otherwise the mtri is NO invertile Hence, the mtri in Emple is not invertile while the mtri in Emple is invertile provided tht we hve Note: When clculting the determinnt of mtri we usully epnd long the row or column contining most zeros in order to minimize the rithmetic So, in Emple we could choose to epnd long row or epnd down column Determinnts nd the Rule of Srrus An lterntive pproch for clculting the determinnt of mtri A c c c ws developed y the French mthemticin Pierre Srrus (798-8) he Rule of Srrus involves the following steps:

26 rewrite the first two columns of the mtri to the right of it c c c c c using the left to right digonls tke the products,, c c c : c c c c c using the right to left digonls tke the products,, c c c, c c c c c comine the ove nd clculte the determinnt s follows: ) det( c c c c c c A he Rule of Srrus is essentilly the sme s the method we descried previously Aside: Geometriclly, the solute vlue of the determinnt of mtri is the volume of prllelepiped whose edges re the vectors u ),, (, v ),, ( nd w ),, ( c c c u v w

27 he inverse of mtri y the cofctor method We now etend the ide of n inverse mtri to the cse In generl, the inverse of mtri A is given y the formul A det ( A) dj ( A) det ( A ) where the mtri dj (A) is known s the djoint mtri of A In order to clculte the inverse of mtri A, if it eists, we must therefore otin the determinnt of A nd the djoint of A he derivtion of the djoint mtri requires us to clculte the mtri of minors of A nd mtri of cofctors of A he following prgrphs illustrte the methodology y wy of n emple reducing the procedure to five distinct steps Emple Determine the inverse of the mtri, A if it eists Solution SEP : Clculte the determinnt of A Epnding long the third row the determinnt of A is det( A ) ( ) Since det( A ), A eists

28 SEP : Clculte the mtri of minors he minor of entry i j, denoted y remove the i th row th remove the j column M i j, is otined s follows: the minor M i j is the determinnt of the remining mtri he minor of entry is: M ( ) he minor of entry is: M he minor of entry is: M he minor of entry is: M he minor of entry is: M ( ) he minor of entry is: M he minor of entry is: M ( ) 7

29 he minor of entry is: M 9 ( ) he minor of entry is: M 8 Hence, the mtri of minors is: SEP : Clculte the cofctor mtri i j he cofctor of entry i j, denoted y C i j, is defined s C i j ( ) M i j o otin the cofctor mtri cof (A) we simply chnge signs of the elements of the mtri of minors clculted in Step using the sign mtri: Hence, we otin the cofctor mtri cof (A) 8

30 9 SEP : Clculte the djoint mtri he djoint of A is defined to e the trnspose of the cofctor mtri, ie (A) dj SEP : Clculte the inverse mtri he inverse of the mtri A is clculted s, ) ( ) det ( A dj A A so tht A which simplifies to give A It is strightforwrd to check tht I A A A A We hve, I A A s required

31 Emple Determine the inverse of the mtri A 9 if it eists 7 Solution SEP : Clculte the determinnt of A Epnding long the first row the determinnt of A is 9 9 det ( A ) ( ) ( ) 7 9 Since det( A ), A eists SEP : Clculte the mtri of minors he minor of entry is: M he minor of entry is: 9 M he minor of entry is: 9 M 9 7 he minor of entry is: M he minor of entry is: M 9 7 7

32 he minor of entry is: M 9 7 he minor of entry is: M 9 ( ) 8 7 he minor of entry is: M he minor of entry is: M 9 ( 9) 9 7 Hence, the mtri of minors is: 8 8 SEP : Clculte the cofctor mtri i j he cofctor of entry i j, denoted y C i j, is defined s C i j ( ) M i j o otin the cofctor mtri cof (A) we simply chnge signs of the elements of the mtri of minors in Step using the sign mtri: Hence, we otin the cofctor mtri cof (A) 8 8

33 SEP : Clculte the djoint mtri he djoint of A is determined s the trnspose of the cofctor mtri, ie 8 dj (A) 8 SEP : Clculte the inverse mtri he inverse of the mtri A is clculted s A dj( A) det ( A) so tht 8 A 8 Check the inverse is correct s follows: 8 A A 9 8 I 7 s required

34 Emple 7 Clculte the determinnt of the mtri, A nd find A if it eists Solution As n lterntive we use the Rule of Srrus to clculte the determinnt Writing det ( A ) As det ( A ) the mtri A is not invertile Aside: Geometriclly the result tht det ( A ) mens tht the vectors (,, ), (,, ), nd (7, 8, 9) re coplnr, ie they lie in the sme plne, so the volume of prllelepiped sed on them is equl to

35 7 Eigenvlues nd eigenvectors of mtri Eigenvlues nd eigenvectors hve mny importnt pplictions in science nd engineering including solving systems of differentil equtions, stility nlysis, virtion nlysis nd modelling popultion dynmics Let A e n n mtri An eigenvlue of A is sclr λ (rel or comple) such tht A λ (I) for some non-zero vector In this cse, we cll the vector n eigenvector of A corresponding to λ Geometriclly Eq (I) mens tht the vectors A nd re prllel he vlue of λ determines wht hppens to when it is multiplied y A, ie whether it is shrunk or stretched or if its direction is unchnged or reversed Emple 8 If A nd, then A Here we hve tht A nd so we sy tht the eigenvlue λ is n eigenvector of A corresponding to he geometric effect in this emple is tht the vector hs een stretched y fctor of ut its direction remins unchnged s λ > Note tht ny sclr multiple of the vector eigenvlue λ is n eigenvector corresponding to the

36 7 Clcultion of eigenvlues If A is mtri it is reltively strightforwrd to clculte its eigenvlues nd eigenvectors y hnd So, how do we clculte them? We know tht I, where I is the identity mtri, so we cn rewrite Eq (I) s A λ I A λ I ( A λ I ) If the mtri ( A λ I) is invertile, ie det( A λ I), then the only solution to the ove eqution is the zero vector, ie We re not interested in this cse s n eigenvector must e non-zero he eqution ( A λ I) cn only hold for non-zero vector if the mtri ( A λ I) is singulr (does not hve n inverse) Hence, the eigenvlues of A re the numers λ for which the mtri ( A λ I) does not hve n inverse In other words the numers λ stisfy the eqution det ( A λ I ) (II) nd they cn e rel or comple

37 7 Rel distinct eigenvlues We firstly look t the cse where n n n mtri hs n distinct eigenvlues Emple 9 Find the eigenvlues of the following mtrices : (i) A (ii) B (iii) C 7 7 Solutions λ (i) A λ I λ 7 7 λ λ Hence, det ( A λ I ) ( λ)( λ) ( )(7) λ λ 7 λ We cll λ λ the chrcteristic polynomil of the mtri A he eigenvlues of A re the roots of the chrcteristic eqution det ( A λ I ), ie λ λ ( λ )( λ ) λ nd λ Hence, λ nd λ re the eigenvlues of the mtri A Note: We cn esily check our nswer s follows: Let tr(a) denote the trce of mtri A, ie the sum of the elements on the min digonl he sum of the eigenvlues of A must equl the trce of the mtri Here we hve tht tr ( A ) ( ) nd the sum of the eigenvlues is, s required

38 (ii) λ B λ I λ 7 7 λ λ Hence, det ( B λ I ) ( λ)(7 λ) ( )( ) λ λ 7 7 λ Now solve det ( B λ I ) to find the eigenvlues of B, ie λ λ 7 ( λ )( λ ) λ nd λ Hence, λ nd λ re the eigenvlues of the mtri B (iii) λ C λ I λ λ λ Hence, det ( C λ I ) ( λ)( λ) ()() λ λ he eigenvlues of C stisfy det ( C λ I ), ie λ λ ± Hence, λ nd λ re the eigenvlues of the mtri C he following emple demonstrtes short-cut pproch tht cn e dopted when clculting the eigenvlues of specific types of mtrices Emple Find the eigenvlues of the following mtrices: (i) 7 A (ii) B (iii) C 8 7

39 In this emple we note tht: mtri A is digonl mtri (see Section ) nd hs the property tht ll of its entries not on the min digonl re mtri B is n upper-tringulr mtri (see Section ) nd hs the property tht ll of its entries elow the min digonl re mtri C is lower-tringulr mtri (see Section ) nd hs the property tht ll of its entries ove the min digonl re Note tht, in ech cse, some of the entries on the min digonl cn e zero Solution In ll three cses digonl, upper-tringulr nd lower tringulr - the eigenvlues re simply the entries on the min digonl nd so we cn just red them off without the need for ny clcultions Hence, he eigenvlues of mtri A re: λ, λ 8 he eigenvlues of mtri B re: λ, λ he eigenvlues of mtri C re: λ, λ We verify our nswers using the method descried erlier λ (i) Solving det( A λ I) gives 8 λ ( λ )(8 λ) λ, λ 8 λ 7 (ii) Solving det( B λ I) gives λ ( λ )( λ) λ, λ λ (ii) Solving det( C λ I) gives λ ( λ)( λ) λ, λ 8

40 7 Repeted eigenvlues In the emples presented up to now the eigenvlues hve een distinct ut it is possile for mtri to hve repeted eigenvlues Emple Find the eigenvlues of the mtri, 9 A 9 Solution o find the eigenvlues we solve λ 9 det ( A λ I ) 9 λ ( λ )(9 λ) 9 λ λ ( λ ) ( λ ) λ (repeted) he eigenvlue λ is sid to hve lgeric multiplicity, ie the numer of times it is root of the chrcteristic eqution 9

41 7 Zero eigenvlues We hve previously noted tht n eigenvector cnnot e the zero vector,, ut it is possile to hve n eigenvlue λ Emple Find the eigenvlues nd eigenvectors of the mtri, A Solution o find the eigenvlues we need to solve λ det ( A λ I ) λ ( λ )( λ) λ 7λ λ ( λ 7) λ, λ 7 his emple shows tht it is possile for to e n eigenvlue of mtri Note tht if is n eigenvlue of mtri then the mtri is not invertile Hence, the mtri A in this emple cnnot e inverted

42 7 Comple eigenvlues of rel mtrices It is possile for rel-vlued mtri to hve comple eigenvlues (nd eigenvectors) s illustrted y the following emple Emple Find the eigenvlues of the mtrices: (i) A (ii) B Solution λ (i) det ( A λ I ) λ λ λ j, λ j λ (ii) det ( B λ I ) λ λ λ Solve using the qudrtic formul, or y completing the squre, to otin, λ j, λ j Note: For mtri with rel entries its comple eigenvlues lwys occur in comple conjugte pirs

43 7 Clcultion of eigenvectors Once we hve clculted the eigenvlues we cn find the eigenvectors y solving the mtri eqution A λ (III) or equivlently, s we sw ove, ( A λ I ) for ech eigenvlue in turn Emple Find the eigenvlues nd eigenvectors of the mtri, 7 A Solution First we find the eigenvlues y solving: λ 7 det ( A λ I ) λ ( λ )( λ) 7 λ λ ( λ )( λ ) λ, λ We now clculte the eigenvectors corresponding to the eigenvlues y solving Eq (III)

44 Cse : o find n eigenvector corresponding to eigenvlue λ we solve, A λ () () hese re simultneous equtions nd we note here tht one eqution will lwys e multiple of the other - if not then you hve mde mistke! Here Eq () is 7 times Eq () Both equtions give If we let α, sy, for some non-zero rel numer α, then α nd we find the first eigenvector to e of the form α α α Note tht there re infinitely mny non-zero eigenvectors depending on the vlue chosen for α Setting α gives n eigenvector corresponding to the eigenvlue λ s We cn check our nswer y showing tht A A 7 nd λ Hence, A λ s required

45 Cse : o find n eigenvector corresponding to eigenvlue λ we solve, A λ Both these equtions give 7 Let α, sy, for some non-zero rel numer α, then 7α nd so 7α α 7 α Setting α gives 7 It is strightforwrd to check tht A In summry, we therefore hve the eigenvlue/eigenvector pirs, λ, ; λ, 7

46 Emple Find the eigenvlues nd eigenvectors of the mtri, B 7 Solution In Emple 9 prt (ii) we found the eigenvlues of B to e λ nd λ We now clculte the eigenvectors corresponding to these eigenvlues y solving the eigenvector eqution, A λ Cse : o find n eigenvector corresponding to eigenvlue λ we solve, A λ Both these equtions give Note tht for μ system we do not ctully need to introduce the prmeter s we did in the previous emple We cn simply choose convenient numericl vlue for either of the components or of the eigenvector So here we cn let, sy, giving hus n eigenvector corresponding to the eigenvlue λ is

47 Cse : o find n eigenvector corresponding to eigenvlue λ we solve A λ Both these equtions give Let, sy, giving hen n eigenvector corresponding to the eigenvlue λ is In summry, we therefore hve the eigenvlue/eigenvector pirs, λ, ; λ, Emple Find the eigenvlues nd eigenvectors of the mtri, A

48 Solution o find the eigenvlues we need to solve λ det ( A λ I) λ ( λ )( λ) λ 7λ λ ( λ 7) λ, λ 7 We now find the eigenvectors: Cse : o find n eigenvector corresponding to eigenvlue λ we solve, A Both these equtions give Let, sy, giving Hence, n eigenvector corresponding to the eigenvlue λ is Cse : o find n eigenvector corresponding to eigenvlue λ 7, solve A 7 7 7

49 7 7 Both these equtions give Let, sy, giving Hence, n eigenvector corresponding to the eigenvlue λ 7 is o summrise we hve: λ, ; λ 7, Emple 7 Find the eigenvectors of the mtri, A Solution In Emple we found tht A hd comple eigenvlues, λ j nd λ j If mtri A with rel entries hs comple eigenvlue λ then we know tht its comple conjugte λ is lso n eigenvlue of A Furthermore, it cn e shown tht if is n eigenvector corresponding to λ then its comple conjugte, formed y tking the comple conjugtes of the entries of, is n eigenvector corresponding to λ We now use this result to find the eigenvectors of the mtri A 8

50 Cse : o find n eigenvector corresponding to eigenvlue λ j we solve A λ j j j If, for emple, we multiply the first eqution y j oth equtions give j Let, sy, then j An eigenvector corresponding to the eigenvlue λ j will then e j Cse : o find n eigenvector corresponding to eigenvlue conjugtes of the entries of giving, j λ j simply tke the comple o summrise we hve: λ j, j ; λ j, j 9

51 7 Some properties of eigenvlues nd eigenvectors Let A e rel n n mtri A will hve ectly n eigenvlues which my e repeted nd will e rel or occur in comple conjugte pirs An eigenvlue cn e zero ut n eigenvector cnnot e the zero vector, he sum of the eigenvlues of A equls the sum of the min digonl entries of A, ie the trce of A he product of the eigenvlues of A equls the determinnt of A If is n eigenvlue of A then A is not invertile If λ is n eigenvlue of n invertile mtri A, with s corresponding eigenvector, then is n eigenvlue of A, gin with s corresponding eigenvector λ k If λ is n eigenvlue of A, with s corresponding eigenvector, then λ is n eigenvlue of k A, gin with s corresponding eigenvector, for ny positive integer k he mtri A nd its trnspose, A, hve the sme eigenvlues ut there is no simple reltionship etween their eigenvectors Summry o clculte the eigenvlues nd eigenvectors of n n mtri A we proceed s follows: Clculte the determinnt of the mtri A λ I, it will e polynomil in λ of degree n Find the roots of the polynomil y solving det ( A λ I ) he n roots of the polynomil re the eigenvlues of the mtri A For ech eigenvlue, λ, solve ( A λ I ) to find n eigenvector

52 utoril Eercises Q Simplify the following: (i) (ii) (iii) (iv) Q Simplify the following mtri products: (i) (ii) (iii) ( ) (iv) ( ) 7 Q Simplify the following nd comment on your nswers: (i) (ii)

53 Q (i) Which of the following mtrices cn e squred?, M A (ii) In generl, which mtrices cn e squred? Q (i) Given tht A, find the inverse mtri A nd clculte the mtri products AA nd A A Comment on your results (ii) Given tht A clculte the mtri product A A Q Determine when the following mtri is invertile nd clculte its inverse: k A Q7 For the mtri A show tht A A ) ( Q8 Let A nd 8 B Evlute B A ) ( nd B A Q9 Let A nd B Evlute ) ( B A nd A B

54 Q Evlute the determinnt of ech of the following mtrices: (i) (ii) (iii) Q Which of the mtrices in Question re invertile? Justify your nswer Q For ech invertile mtri in Question determine the inverse Q Given tht A, find the inverse mtri A nd clculte the mtri products AA nd A A Q Given tht D, find the inverse mtri D Q Consider the mtrices D nd 8 P Determine the inverse mtri P nd clculte the mtri product P P D A

55 Q Find the eigenvlues of ech of the following mtrices: (i) (ii) (iii) Q7 Find the eigenvlues nd eigenvectors of ech of the following mtrices: (i) (ii) (iii) (iv) (v) (vi) (vii) 7 (viii) 7 (i) ()

56 Answers S (i) ; (ii), (iii) ; (iv) S (i) ; (ii) 8 9 ; (iii) 9 (iv) S (i) (ii) 8 he conclusion from this emple is tht mtri multipliction is not commuttive, so tht the order in which mtrices re multiplied is importnt S (i) Only the first mtri, A, cn e squred since it is conformle for multipliction with itself (ii) In generl, to squre mtri of size p m requires multiplying n p m mtri y n p m mtri hese re only conformle for mtri multipliction if p m S (i) A so det(a) which is non-zero nd so the mtri is invertile hen A We hve tht I A A AA Both mtri products give the identity mtri

57 (ii) A so A nd 9 AA M S k A so k A ) det( he mtri A is invertile provided ) det( A, ie provided k In this cse the inverse is, k k A S7 A hen A A ) ( s required S8 8 8 B A 8 B A so B A B A 8 ) ( In generl for mtrices A nd B we hve tht B A B A ) ( S9 7 8 B A nd so 8 7 ) ( B A Also, A nd B so ) ( 8 7 B A A B In generl for n n squre mtrices A nd B we hve tht, ) ( A B B A

58 7 S We shll epnd on Row throughout ut note tht we could epnd on ny row or column nd the determinnt of the mtri would e the sme in ech cse (i) D (ii) D (iii) D S hey re ll invertile ecept (iii), since only (iii) hs zero determinnt S (i) (ii) S A ; AA A A S D

59 Note: If D n n is n n digonl mtri then its inverse is given y D n n provided tht none of the digonl elements re zero S P nd A P D P Note: We shll see lter tht the mtri D hs the eigenvlues of A on its min digonl while the columns of P contin the corresponding eigenvectors written in the sme order s the eigenvlues pper in D he process of clculting the mtrices P nd D is clled digonlistion S (i) λ, λ (ii) λ, λ (iii) λ j, λ j 8

60 S7 (i) λ, λ, (ii) λ, ; λ, (iii) λ, ; λ, (iv) λ, ; λ, (v) λ, ; λ 8, (vi) λ, ; λ, (vii) λ, ; λ, 7 (viii) λ, ; λ 7, (i) λ, ; λ, () λ, ; λ, 9

SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics

SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics SCHOOL OF ENGINEERING & BUIL ENVIRONMEN Mthemtics An Introduction to Mtrices Definition of Mtri Size of Mtri Rows nd Columns of Mtri Mtri Addition Sclr Multipliction of Mtri Mtri Multipliction 7 rnspose

More information

Matrices SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics (c) 1. Definition of a Matrix

Matrices SCHOOL OF ENGINEERING & BUILT ENVIRONMENT. Mathematics (c) 1. Definition of a Matrix tries Definition of tri mtri is regulr rry of numers enlosed inside rkets SCHOOL OF ENGINEERING & UIL ENVIRONEN Emple he following re ll mtries: ), ) 9, themtis ), d) tries Definition of tri Size of tri

More information

Matrix Algebra. Matrix Addition, Scalar Multiplication and Transposition. Linear Algebra I 24

Matrix Algebra. Matrix Addition, Scalar Multiplication and Transposition. Linear Algebra I 24 Mtrix lger Mtrix ddition, Sclr Multipliction nd rnsposition Mtrix lger Section.. Mtrix ddition, Sclr Multipliction nd rnsposition rectngulr rry of numers is clled mtrix ( the plurl is mtrices ) nd the

More information

Lecture Solution of a System of Linear Equation

Lecture Solution of a System of Linear Equation ChE Lecture Notes, Dept. of Chemicl Engineering, Univ. of TN, Knoville - D. Keffer, 5/9/98 (updted /) Lecture 8- - Solution of System of Liner Eqution 8. Why is it importnt to e le to solve system of liner

More information

September 13 Homework Solutions

September 13 Homework Solutions College of Engineering nd Computer Science Mechnicl Engineering Deprtment Mechnicl Engineering 5A Seminr in Engineering Anlysis Fll Ticket: 5966 Instructor: Lrry Cretto Septemer Homework Solutions. Are

More information

INTRODUCTION TO LINEAR ALGEBRA

INTRODUCTION TO LINEAR ALGEBRA ME Applied Mthemtics for Mechnicl Engineers INTRODUCTION TO INEAR AGEBRA Mtrices nd Vectors Prof. Dr. Bülent E. Pltin Spring Sections & / ME Applied Mthemtics for Mechnicl Engineers INTRODUCTION TO INEAR

More information

Chapter 3 MATRIX. In this chapter: 3.1 MATRIX NOTATION AND TERMINOLOGY

Chapter 3 MATRIX. In this chapter: 3.1 MATRIX NOTATION AND TERMINOLOGY Chpter 3 MTRIX In this chpter: Definition nd terms Specil Mtrices Mtrix Opertion: Trnspose, Equlity, Sum, Difference, Sclr Multipliction, Mtrix Multipliction, Determinnt, Inverse ppliction of Mtrix in

More information

The Algebra (al-jabr) of Matrices

The Algebra (al-jabr) of Matrices Section : Mtri lgebr nd Clculus Wshkewicz College of Engineering he lgebr (l-jbr) of Mtrices lgebr s brnch of mthemtics is much broder thn elementry lgebr ll of us studied in our high school dys. In sense

More information

2. VECTORS AND MATRICES IN 3 DIMENSIONS

2. VECTORS AND MATRICES IN 3 DIMENSIONS 2 VECTORS AND MATRICES IN 3 DIMENSIONS 21 Extending the Theory of 2-dimensionl Vectors x A point in 3-dimensionl spce cn e represented y column vector of the form y z z-xis y-xis z x y x-xis Most of the

More information

Matrices. Elementary Matrix Theory. Definition of a Matrix. Matrix Elements:

Matrices. Elementary Matrix Theory. Definition of a Matrix. Matrix Elements: Mtrices Elementry Mtrix Theory It is often desirble to use mtrix nottion to simplify complex mthemticl expressions. The simplifying mtrix nottion usully mkes the equtions much esier to hndle nd mnipulte.

More information

THE DISCRIMINANT & ITS APPLICATIONS

THE DISCRIMINANT & ITS APPLICATIONS THE DISCRIMINANT & ITS APPLICATIONS The discriminnt ( Δ ) is the epression tht is locted under the squre root sign in the qudrtic formul i.e. Δ b c. For emple: Given +, Δ () ( )() The discriminnt is used

More information

Vectors , (0,0). 5. A vector is commonly denoted by putting an arrow above its symbol, as in the picture above. Here are some 3-dimensional vectors:

Vectors , (0,0). 5. A vector is commonly denoted by putting an arrow above its symbol, as in the picture above. Here are some 3-dimensional vectors: Vectors 1-23-2018 I ll look t vectors from n lgeric point of view nd geometric point of view. Algericlly, vector is n ordered list of (usully) rel numers. Here re some 2-dimensionl vectors: (2, 3), ( )

More information

Things to Memorize: A Partial List. January 27, 2017

Things to Memorize: A Partial List. January 27, 2017 Things to Memorize: A Prtil List Jnury 27, 2017 Chpter 2 Vectors - Bsic Fcts A vector hs mgnitude (lso clled size/length/norm) nd direction. It does not hve fixed position, so the sme vector cn e moved

More information

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique? XII. LINEAR ALGEBRA: SOLVING SYSTEMS OF EQUATIONS Tody we re going to tlk out solving systems of liner equtions. These re prolems tht give couple of equtions with couple of unknowns, like: 6= x + x 7=

More information

Lecture 3. In this lecture, we will discuss algorithms for solving systems of linear equations.

Lecture 3. In this lecture, we will discuss algorithms for solving systems of linear equations. Lecture 3 3 Solving liner equtions In this lecture we will discuss lgorithms for solving systems of liner equtions Multiplictive identity Let us restrict ourselves to considering squre mtrices since one

More information

Matrices and Determinants

Matrices and Determinants Nme Chpter 8 Mtrices nd Determinnts Section 8.1 Mtrices nd Systems of Equtions Objective: In this lesson you lerned how to use mtrices, Gussin elimintion, nd Guss-Jordn elimintion to solve systems of liner

More information

MATHEMATICS FOR MANAGEMENT BBMP1103

MATHEMATICS FOR MANAGEMENT BBMP1103 T o p i c M T R I X MTHEMTICS FOR MNGEMENT BBMP Ojectives: TOPIC : MTRIX. Define mtri. ssess the clssifictions of mtrices s well s know how to perform its opertions. Clculte the determinnt for squre mtri

More information

Chapter 2. Determinants

Chapter 2. Determinants Chpter Determinnts The Determinnt Function Recll tht the X mtrix A c b d is invertible if d-bc0. The expression d-bc occurs so frequently tht it hs nme; it is clled the determinnt of the mtrix A nd is

More information

CHAPTER 1 PROGRAM OF MATRICES

CHAPTER 1 PROGRAM OF MATRICES CHPTER PROGRM OF MTRICES -- INTRODUCTION definition of engineering is the science y which the properties of mtter nd sources of energy in nture re mde useful to mn. Thus n engineer will hve to study the

More information

Quadratic Forms. Quadratic Forms

Quadratic Forms. Quadratic Forms Qudrtic Forms Recll the Simon & Blume excerpt from n erlier lecture which sid tht the min tsk of clculus is to pproximte nonliner functions with liner functions. It s ctully more ccurte to sy tht we pproximte

More information

Algebra Of Matrices & Determinants

Algebra Of Matrices & Determinants lgebr Of Mtrices & Determinnts Importnt erms Definitions & Formule 0 Mtrix - bsic introduction: mtrix hving m rows nd n columns is clled mtrix of order m n (red s m b n mtrix) nd mtrix of order lso in

More information

Analytically, vectors will be represented by lowercase bold-face Latin letters, e.g. a, r, q.

Analytically, vectors will be represented by lowercase bold-face Latin letters, e.g. a, r, q. 1.1 Vector Alger 1.1.1 Sclrs A physicl quntity which is completely descried y single rel numer is clled sclr. Physiclly, it is something which hs mgnitude, nd is completely descried y this mgnitude. Exmples

More information

DETERMINANTS. All Mathematical truths are relative and conditional. C.P. STEINMETZ

DETERMINANTS. All Mathematical truths are relative and conditional. C.P. STEINMETZ All Mthemticl truths re reltive nd conditionl. C.P. STEINMETZ 4. Introduction DETERMINANTS In the previous chpter, we hve studied bout mtrices nd lgebr of mtrices. We hve lso lernt tht system of lgebric

More information

Determinants Chapter 3

Determinants Chapter 3 Determinnts hpter Specil se : x Mtrix Definition : the determinnt is sclr quntity defined for ny squre n x n mtrix nd denoted y or det(). x se ecll : this expression ppers in the formul for x mtrix inverse!

More information

Bases for Vector Spaces

Bases for Vector Spaces Bses for Vector Spces 2-26-25 A set is independent if, roughly speking, there is no redundncy in the set: You cn t uild ny vector in the set s liner comintion of the others A set spns if you cn uild everything

More information

Elements of Matrix Algebra

Elements of Matrix Algebra Elements of Mtrix Algebr Klus Neusser Kurt Schmidheiny September 30, 2015 Contents 1 Definitions 2 2 Mtrix opertions 3 3 Rnk of Mtrix 5 4 Specil Functions of Qudrtic Mtrices 6 4.1 Trce of Mtrix.........................

More information

Chapter 5 Determinants

Chapter 5 Determinants hpter 5 Determinnts 5. Introduction Every squre mtri hs ssocited with it sclr clled its determinnt. Given mtri, we use det() or to designte its determinnt. We cn lso designte the determinnt of mtri by

More information

set is not closed under matrix [ multiplication, ] and does not form a group.

set is not closed under matrix [ multiplication, ] and does not form a group. Prolem 2.3: Which of the following collections of 2 2 mtrices with rel entries form groups under [ mtrix ] multipliction? i) Those of the form for which c d 2 Answer: The set of such mtrices is not closed

More information

Rudimentary Matrix Algebra

Rudimentary Matrix Algebra Rudimentry Mtrix Alger Mrk Sullivn Decemer 4, 217 i Contents 1 Preliminries 1 1.1 Why does this document exist?.................... 1 1.2 Why does nyone cre out mtrices?................ 1 1.3 Wht is mtrix?...........................

More information

ECON 331 Lecture Notes: Ch 4 and Ch 5

ECON 331 Lecture Notes: Ch 4 and Ch 5 Mtrix Algebr ECON 33 Lecture Notes: Ch 4 nd Ch 5. Gives us shorthnd wy of writing lrge system of equtions.. Allows us to test for the existnce of solutions to simultneous systems. 3. Allows us to solve

More information

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac

ARITHMETIC OPERATIONS. The real numbers have the following properties: a b c ab ac REVIEW OF ALGEBRA Here we review the bsic rules nd procedures of lgebr tht you need to know in order to be successful in clculus. ARITHMETIC OPERATIONS The rel numbers hve the following properties: b b

More information

Here we study square linear systems and properties of their coefficient matrices as they relate to the solution set of the linear system.

Here we study square linear systems and properties of their coefficient matrices as they relate to the solution set of the linear system. Section 24 Nonsingulr Liner Systems Here we study squre liner systems nd properties of their coefficient mtrices s they relte to the solution set of the liner system Let A be n n Then we know from previous

More information

Parse trees, ambiguity, and Chomsky normal form

Parse trees, ambiguity, and Chomsky normal form Prse trees, miguity, nd Chomsky norml form In this lecture we will discuss few importnt notions connected with contextfree grmmrs, including prse trees, miguity, nd specil form for context-free grmmrs

More information

Chapters Five Notes SN AA U1C5

Chapters Five Notes SN AA U1C5 Chpters Five Notes SN AA U1C5 Nme Period Section 5-: Fctoring Qudrtic Epressions When you took lger, you lerned tht the first thing involved in fctoring is to mke sure to fctor out ny numers or vriles

More information

dx dt dy = G(t, x, y), dt where the functions are defined on I Ω, and are locally Lipschitz w.r.t. variable (x, y) Ω.

dx dt dy = G(t, x, y), dt where the functions are defined on I Ω, and are locally Lipschitz w.r.t. variable (x, y) Ω. Chpter 8 Stility theory We discuss properties of solutions of first order two dimensionl system, nd stility theory for specil clss of liner systems. We denote the independent vrile y t in plce of x, nd

More information

Linear Inequalities. Work Sheet 1

Linear Inequalities. Work Sheet 1 Work Sheet 1 Liner Inequlities Rent--Hep, cr rentl compny,chrges $ 15 per week plus $ 0.0 per mile to rent one of their crs. Suppose you re limited y how much money you cn spend for the week : You cn spend

More information

LINEAR ALGEBRA APPLIED

LINEAR ALGEBRA APPLIED 5.5 Applictions of Inner Product Spces 5.5 Applictions of Inner Product Spces 7 Find the cross product of two vectors in R. Find the liner or qudrtic lest squres pproimtion of function. Find the nth-order

More information

Matrix Eigenvalues and Eigenvectors September 13, 2017

Matrix Eigenvalues and Eigenvectors September 13, 2017 Mtri Eigenvlues nd Eigenvectors September, 7 Mtri Eigenvlues nd Eigenvectors Lrry Cretto Mechnicl Engineering 5A Seminr in Engineering Anlysis September, 7 Outline Review lst lecture Definition of eigenvlues

More information

Chapter 8.2: The Integral

Chapter 8.2: The Integral Chpter 8.: The Integrl You cn think of Clculus s doule-wide triler. In one width of it lives differentil clculus. In the other hlf lives wht is clled integrl clculus. We hve lredy eplored few rooms in

More information

Chapter 1: Logarithmic functions and indices

Chapter 1: Logarithmic functions and indices Chpter : Logrithmic functions nd indices. You cn simplify epressions y using rules of indices m n m n m n m n ( m ) n mn m m m m n m m n Emple Simplify these epressions: 5 r r c 4 4 d 6 5 e ( ) f ( ) 4

More information

MATRICES AND VECTORS SPACE

MATRICES AND VECTORS SPACE MATRICES AND VECTORS SPACE MATRICES AND MATRIX OPERATIONS SYSTEM OF LINEAR EQUATIONS DETERMINANTS VECTORS IN -SPACE AND -SPACE GENERAL VECTOR SPACES INNER PRODUCT SPACES EIGENVALUES, EIGENVECTORS LINEAR

More information

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3 2 The Prllel Circuit Electric Circuits: Figure 2- elow show ttery nd multiple resistors rrnged in prllel. Ech resistor receives portion of the current from the ttery sed on its resistnce. The split is

More information

HW3, Math 307. CSUF. Spring 2007.

HW3, Math 307. CSUF. Spring 2007. HW, Mth 7. CSUF. Spring 7. Nsser M. Abbsi Spring 7 Compiled on November 5, 8 t 8:8m public Contents Section.6, problem Section.6, problem Section.6, problem 5 Section.6, problem 7 6 5 Section.6, problem

More information

Chapter 6 Techniques of Integration

Chapter 6 Techniques of Integration MA Techniques of Integrtion Asst.Prof.Dr.Suprnee Liswdi Chpter 6 Techniques of Integrtion Recll: Some importnt integrls tht we hve lernt so fr. Tle of Integrls n+ n d = + C n + e d = e + C ( n ) d = ln

More information

8. Complex Numbers. We can combine the real numbers with this new imaginary number to form the complex numbers.

8. Complex Numbers. We can combine the real numbers with this new imaginary number to form the complex numbers. 8. Complex Numers The rel numer system is dequte for solving mny mthemticl prolems. But it is necessry to extend the rel numer system to solve numer of importnt prolems. Complex numers do not chnge the

More information

Chapter 9 Definite Integrals

Chapter 9 Definite Integrals Chpter 9 Definite Integrls In the previous chpter we found how to tke n ntiderivtive nd investigted the indefinite integrl. In this chpter the connection etween ntiderivtives nd definite integrls is estlished

More information

4 VECTORS. 4.0 Introduction. Objectives. Activity 1

4 VECTORS. 4.0 Introduction. Objectives. Activity 1 4 VECTRS Chpter 4 Vectors jectives fter studying this chpter you should understnd the difference etween vectors nd sclrs; e le to find the mgnitude nd direction of vector; e le to dd vectors, nd multiply

More information

Coalgebra, Lecture 15: Equations for Deterministic Automata

Coalgebra, Lecture 15: Equations for Deterministic Automata Colger, Lecture 15: Equtions for Deterministic Automt Julin Slmnc (nd Jurrin Rot) Decemer 19, 2016 In this lecture, we will study the concept of equtions for deterministic utomt. The notes re self contined

More information

Chapter 4 Contravariance, Covariance, and Spacetime Diagrams

Chapter 4 Contravariance, Covariance, and Spacetime Diagrams Chpter 4 Contrvrince, Covrince, nd Spcetime Digrms 4. The Components of Vector in Skewed Coordintes We hve seen in Chpter 3; figure 3.9, tht in order to show inertil motion tht is consistent with the Lorentz

More information

Math 520 Final Exam Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008

Math 520 Final Exam Topic Outline Sections 1 3 (Xiao/Dumas/Liaw) Spring 2008 Mth 520 Finl Exm Topic Outline Sections 1 3 (Xio/Dums/Liw) Spring 2008 The finl exm will be held on Tuesdy, My 13, 2-5pm in 117 McMilln Wht will be covered The finl exm will cover the mteril from ll of

More information

Bridging the gap: GCSE AS Level

Bridging the gap: GCSE AS Level Bridging the gp: GCSE AS Level CONTENTS Chpter Removing rckets pge Chpter Liner equtions Chpter Simultneous equtions 8 Chpter Fctors 0 Chpter Chnge the suject of the formul Chpter 6 Solving qudrtic equtions

More information

Introduction To Matrices MCV 4UI Assignment #1

Introduction To Matrices MCV 4UI Assignment #1 Introduction To Mtrices MCV UI Assignment # INTRODUCTION: A mtrix plurl: mtrices) is rectngulr rry of numbers rrnged in rows nd columns Exmples: ) b) c) [ ] d) Ech number ppering in the rry is sid to be

More information

2.4 Linear Inequalities and Interval Notation

2.4 Linear Inequalities and Interval Notation .4 Liner Inequlities nd Intervl Nottion We wnt to solve equtions tht hve n inequlity symol insted of n equl sign. There re four inequlity symols tht we will look t: Less thn , Less thn or

More information

Mathematics. Area under Curve.

Mathematics. Area under Curve. Mthemtics Are under Curve www.testprepkrt.com Tle of Content 1. Introduction.. Procedure of Curve Sketching. 3. Sketching of Some common Curves. 4. Are of Bounded Regions. 5. Sign convention for finding

More information

308K. 1 Section 3.2. Zelaya Eufemia. 1. Example 1: Multiplication of Matrices: X Y Z R S R S X Y Z. By associativity we have to choices:

308K. 1 Section 3.2. Zelaya Eufemia. 1. Example 1: Multiplication of Matrices: X Y Z R S R S X Y Z. By associativity we have to choices: 8K Zely Eufemi Section 2 Exmple : Multipliction of Mtrices: X Y Z T c e d f 2 R S X Y Z 2 c e d f 2 R S 2 By ssocitivity we hve to choices: OR: X Y Z R S cr ds er fs X cy ez X dy fz 2 R S 2 Suggestion

More information

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique? XII. LINEAR ALGEBRA: SOLVING SYSTEMS OF EQUATIONS Tody we re going to tlk bout solving systems of liner equtions. These re problems tht give couple of equtions with couple of unknowns, like: 6 2 3 7 4

More information

AQA Further Pure 1. Complex Numbers. Section 1: Introduction to Complex Numbers. The number system

AQA Further Pure 1. Complex Numbers. Section 1: Introduction to Complex Numbers. The number system Complex Numbers Section 1: Introduction to Complex Numbers Notes nd Exmples These notes contin subsections on The number system Adding nd subtrcting complex numbers Multiplying complex numbers Complex

More information

M344 - ADVANCED ENGINEERING MATHEMATICS

M344 - ADVANCED ENGINEERING MATHEMATICS M3 - ADVANCED ENGINEERING MATHEMATICS Lecture 18: Lplce s Eqution, Anltic nd Numericl Solution Our emple of n elliptic prtil differentil eqution is Lplce s eqution, lso clled the Diffusion Eqution. If

More information

Review of Gaussian Quadrature method

Review of Gaussian Quadrature method Review of Gussin Qudrture method Nsser M. Asi Spring 006 compiled on Sundy Decemer 1, 017 t 09:1 PM 1 The prolem To find numericl vlue for the integrl of rel vlued function of rel vrile over specific rnge

More information

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives

Properties of Integrals, Indefinite Integrals. Goals: Definition of the Definite Integral Integral Calculations using Antiderivatives Block #6: Properties of Integrls, Indefinite Integrls Gols: Definition of the Definite Integrl Integrl Clcultions using Antiderivtives Properties of Integrls The Indefinite Integrl 1 Riemnn Sums - 1 Riemnn

More information

1 ELEMENTARY ALGEBRA and GEOMETRY READINESS DIAGNOSTIC TEST PRACTICE

1 ELEMENTARY ALGEBRA and GEOMETRY READINESS DIAGNOSTIC TEST PRACTICE ELEMENTARY ALGEBRA nd GEOMETRY READINESS DIAGNOSTIC TEST PRACTICE Directions: Study the exmples, work the prolems, then check your nswers t the end of ech topic. If you don t get the nswer given, check

More information

MATRIX DEFINITION A matrix is any doubly subscripted array of elements arranged in rows and columns.

MATRIX DEFINITION A matrix is any doubly subscripted array of elements arranged in rows and columns. 4.5 THEORETICL SOIL MECHNICS Vector nd Mtrix lger Review MTRIX DEFINITION mtrix is ny douly suscripted rry of elements rrnged in rows nd columns. m - Column Revised /0 n -Row m,,,,,, n n mn ij nd Order

More information

Section 4: Integration ECO4112F 2011

Section 4: Integration ECO4112F 2011 Reding: Ching Chpter Section : Integrtion ECOF Note: These notes do not fully cover the mteril in Ching, ut re ment to supplement your reding in Ching. Thus fr the optimistion you hve covered hs een sttic

More information

The First Fundamental Theorem of Calculus. If f(x) is continuous on [a, b] and F (x) is any antiderivative. f(x) dx = F (b) F (a).

The First Fundamental Theorem of Calculus. If f(x) is continuous on [a, b] and F (x) is any antiderivative. f(x) dx = F (b) F (a). The Fundmentl Theorems of Clculus Mth 4, Section 0, Spring 009 We now know enough bout definite integrls to give precise formultions of the Fundmentl Theorems of Clculus. We will lso look t some bsic emples

More information

Geometric Sequences. Geometric Sequence a sequence whose consecutive terms have a common ratio.

Geometric Sequences. Geometric Sequence a sequence whose consecutive terms have a common ratio. Geometric Sequences Geometric Sequence sequence whose consecutive terms hve common rtio. Geometric Sequence A sequence is geometric if the rtios of consecutive terms re the sme. 2 3 4... 2 3 The number

More information

Operations with Polynomials

Operations with Polynomials 38 Chpter P Prerequisites P.4 Opertions with Polynomils Wht you should lern: How to identify the leding coefficients nd degrees of polynomils How to dd nd subtrct polynomils How to multiply polynomils

More information

The practical version

The practical version Roerto s Notes on Integrl Clculus Chpter 4: Definite integrls nd the FTC Section 7 The Fundmentl Theorem of Clculus: The prcticl version Wht you need to know lredy: The theoreticl version of the FTC. Wht

More information

1B40 Practical Skills

1B40 Practical Skills B40 Prcticl Skills Comining uncertinties from severl quntities error propgtion We usully encounter situtions where the result of n experiment is given in terms of two (or more) quntities. We then need

More information

CSCI 5525 Machine Learning

CSCI 5525 Machine Learning CSCI 555 Mchine Lerning Some Deini*ons Qudrtic Form : nn squre mtri R n n : n vector R n the qudrtic orm: It is sclr vlue. We oten implicitly ssume tht is symmetric since / / I we write it s the elements

More information

Section 6.1 INTRO to LAPLACE TRANSFORMS

Section 6.1 INTRO to LAPLACE TRANSFORMS Section 6. INTRO to LAPLACE TRANSFORMS Key terms: Improper Integrl; diverge, converge A A f(t)dt lim f(t)dt Piecewise Continuous Function; jump discontinuity Function of Exponentil Order Lplce Trnsform

More information

Mathematics Number: Logarithms

Mathematics Number: Logarithms plce of mind F A C U L T Y O F E D U C A T I O N Deprtment of Curriculum nd Pedgogy Mthemtics Numer: Logrithms Science nd Mthemtics Eduction Reserch Group Supported y UBC Teching nd Lerning Enhncement

More information

p-adic Egyptian Fractions

p-adic Egyptian Fractions p-adic Egyptin Frctions Contents 1 Introduction 1 2 Trditionl Egyptin Frctions nd Greedy Algorithm 2 3 Set-up 3 4 p-greedy Algorithm 5 5 p-egyptin Trditionl 10 6 Conclusion 1 Introduction An Egyptin frction

More information

A matrix is a set of numbers or symbols arranged in a square or rectangular array of m rows and n columns as

A matrix is a set of numbers or symbols arranged in a square or rectangular array of m rows and n columns as RMI University ENDIX MRIX GEBR INRDUCIN Mtrix lgebr is powerful mthemticl tool, which is extremely useful in modern computtionl techniques pplicble to sptil informtion science. It is neither new nor difficult,

More information

Goals: Determine how to calculate the area described by a function. Define the definite integral. Explore the relationship between the definite

Goals: Determine how to calculate the area described by a function. Define the definite integral. Explore the relationship between the definite Unit #8 : The Integrl Gols: Determine how to clculte the re described by function. Define the definite integrl. Eplore the reltionship between the definite integrl nd re. Eplore wys to estimte the definite

More information

UNIT 5 QUADRATIC FUNCTIONS Lesson 3: Creating Quadratic Equations in Two or More Variables Instruction

UNIT 5 QUADRATIC FUNCTIONS Lesson 3: Creating Quadratic Equations in Two or More Variables Instruction Lesson 3: Creting Qudrtic Equtions in Two or More Vriles Prerequisite Skills This lesson requires the use of the following skill: solving equtions with degree of Introduction 1 The formul for finding the

More information

Operations with Matrices

Operations with Matrices Section. Equlit of Mtrices Opertions with Mtrices There re three ws to represent mtri.. A mtri cn be denoted b n uppercse letter, such s A, B, or C.. A mtri cn be denoted b representtive element enclosed

More information

STRAND J: TRANSFORMATIONS, VECTORS and MATRICES

STRAND J: TRANSFORMATIONS, VECTORS and MATRICES Mthemtics SKE: STRN J STRN J: TRNSFORMTIONS, VETORS nd MTRIES J3 Vectors Text ontents Section J3.1 Vectors nd Sclrs * J3. Vectors nd Geometry Mthemtics SKE: STRN J J3 Vectors J3.1 Vectors nd Sclrs Vectors

More information

Calculus Module C21. Areas by Integration. Copyright This publication The Northern Alberta Institute of Technology All Rights Reserved.

Calculus Module C21. Areas by Integration. Copyright This publication The Northern Alberta Institute of Technology All Rights Reserved. Clculus Module C Ares Integrtion Copright This puliction The Northern Alert Institute of Technolog 7. All Rights Reserved. LAST REVISED Mrch, 9 Introduction to Ares Integrtion Sttement of Prerequisite

More information

CHAPTER 2d. MATRICES

CHAPTER 2d. MATRICES CHPTER d. MTRICES University of Bhrin Deprtment of Civil nd rch. Engineering CEG -Numericl Methods in Civil Engineering Deprtment of Civil Engineering University of Bhrin Every squre mtrix hs ssocited

More information

Interpreting Integrals and the Fundamental Theorem

Interpreting Integrals and the Fundamental Theorem Interpreting Integrls nd the Fundmentl Theorem Tody, we go further in interpreting the mening of the definite integrl. Using Units to Aid Interprettion We lredy know tht if f(t) is the rte of chnge of

More information

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions

Physics 116C Solution of inhomogeneous ordinary differential equations using Green s functions Physics 6C Solution of inhomogeneous ordinry differentil equtions using Green s functions Peter Young November 5, 29 Homogeneous Equtions We hve studied, especilly in long HW problem, second order liner

More information

Boolean Algebra. Boolean Algebra

Boolean Algebra. Boolean Algebra Boolen Alger Boolen Alger A Boolen lger is set B of vlues together with: - two inry opertions, commonly denoted y + nd, - unry opertion, usully denoted y ˉ or ~ or, - two elements usully clled zero nd

More information

Introduction to Algebra - Part 2

Introduction to Algebra - Part 2 Alger Module A Introduction to Alger - Prt Copright This puliction The Northern Alert Institute of Technolog 00. All Rights Reserved. LAST REVISED Oct., 008 Introduction to Alger - Prt Sttement of Prerequisite

More information

Module 6: LINEAR TRANSFORMATIONS

Module 6: LINEAR TRANSFORMATIONS Module 6: LINEAR TRANSFORMATIONS. Trnsformtions nd mtrices Trnsformtions re generliztions of functions. A vector x in some set S n is mpped into m nother vector y T( x). A trnsformtion is liner if, for

More information

A-Level Mathematics Transition Task (compulsory for all maths students and all further maths student)

A-Level Mathematics Transition Task (compulsory for all maths students and all further maths student) A-Level Mthemtics Trnsition Tsk (compulsory for ll mths students nd ll further mths student) Due: st Lesson of the yer. Length: - hours work (depending on prior knowledge) This trnsition tsk provides revision

More information

LINEAR ALGEBRA AND MATRICES. n ij. is called the main diagonal or principal diagonal of A. A column vector is a matrix that has only one column.

LINEAR ALGEBRA AND MATRICES. n ij. is called the main diagonal or principal diagonal of A. A column vector is a matrix that has only one column. PART 1 LINEAR ALGEBRA AND MATRICES Generl Nottions Mtri (denoted by cpitl boldfce letter) A is n m n mtri. 11 1... 1 n 1... n A ij...... m1 m... mn ij denotes the component t row i nd column j of A. If

More information

Vectors. Introduction. Definition. The Two Components of a Vector. Vectors

Vectors. Introduction. Definition. The Two Components of a Vector. Vectors Vectors Introduction This pper covers generl description of vectors first (s cn e found in mthemtics ooks) nd will stry into the more prcticl res of grphics nd nimtion. Anyone working in grphics sujects

More information

MATH 573 FINAL EXAM. May 30, 2007

MATH 573 FINAL EXAM. May 30, 2007 MATH 573 FINAL EXAM My 30, 007 NAME: Solutions 1. This exm is due Wednesdy, June 6 efore the 1:30 pm. After 1:30 pm I will NOT ccept the exm.. This exm hs 1 pges including this cover. There re 10 prolems.

More information

Chapter 2. Vectors. 2.1 Vectors Scalars and Vectors

Chapter 2. Vectors. 2.1 Vectors Scalars and Vectors Chpter 2 Vectors 2.1 Vectors 2.1.1 Sclrs nd Vectors A vector is quntity hving both mgnitude nd direction. Emples of vector quntities re velocity, force nd position. One cn represent vector in n-dimensionl

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 2

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 2 CS434/54: Pttern Recognition Prof. Olg Veksler Lecture Outline Review of Liner Algebr vectors nd mtrices products nd norms vector spces nd liner trnsformtions eigenvlues nd eigenvectors Introduction to

More information

MT Integral equations

MT Integral equations MT58 - Integrl equtions Introduction Integrl equtions occur in vriety of pplictions, often eing otined from differentil eqution. The reson for doing this is tht it my mke solution of the prolem esier or,

More information

Introduction to Group Theory

Introduction to Group Theory Introduction to Group Theory Let G be n rbitrry set of elements, typiclly denoted s, b, c,, tht is, let G = {, b, c, }. A binry opertion in G is rule tht ssocites with ech ordered pir (,b) of elements

More information

The Fundamental Theorem of Algebra

The Fundamental Theorem of Algebra The Fundmentl Theorem of Alger Jeremy J. Fries In prtil fulfillment of the requirements for the Mster of Arts in Teching with Speciliztion in the Teching of Middle Level Mthemtics in the Deprtment of Mthemtics.

More information

Duality # Second iteration for HW problem. Recall our LP example problem we have been working on, in equality form, is given below.

Duality # Second iteration for HW problem. Recall our LP example problem we have been working on, in equality form, is given below. Dulity #. Second itertion for HW problem Recll our LP emple problem we hve been working on, in equlity form, is given below.,,,, 8 m F which, when written in slightly different form, is 8 F Recll tht we

More information

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals

AP Calculus BC Chapter 8: Integration Techniques, L Hopital s Rule and Improper Integrals AP Clulus BC Chpter 8: Integrtion Tehniques, L Hopitl s Rule nd Improper Integrls 8. Bsi Integrtion Rules In this setion we will review vrious integrtion strtegies. Strtegies: I. Seprte the integrnd into

More information

Math 017. Materials With Exercises

Math 017. Materials With Exercises Mth 07 Mterils With Eercises Jul 0 TABLE OF CONTENTS Lesson Vriles nd lgeric epressions; Evlution of lgeric epressions... Lesson Algeric epressions nd their evlutions; Order of opertions....... Lesson

More information

Numerical Linear Algebra Assignment 008

Numerical Linear Algebra Assignment 008 Numericl Liner Algebr Assignment 008 Nguyen Qun B Hong Students t Fculty of Mth nd Computer Science, Ho Chi Minh University of Science, Vietnm emil. nguyenqunbhong@gmil.com blog. http://hongnguyenqunb.wordpress.com

More information

Matrix & Vector Basic Linear Algebra & Calculus

Matrix & Vector Basic Linear Algebra & Calculus Mtrix & Vector Bsic Liner lgebr & lculus Wht is mtrix? rectngulr rry of numbers (we will concentrte on rel numbers). nxm mtrix hs n rows n m columns M x4 M M M M M M M M M M M M 4 4 4 First row Secon row

More information

Lecture 3: Equivalence Relations

Lecture 3: Equivalence Relations Mthcmp Crsh Course Instructor: Pdric Brtlett Lecture 3: Equivlence Reltions Week 1 Mthcmp 2014 In our lst three tlks of this clss, we shift the focus of our tlks from proof techniques to proof concepts

More information

Genetic Programming. Outline. Evolutionary Strategies. Evolutionary strategies Genetic programming Summary

Genetic Programming. Outline. Evolutionary Strategies. Evolutionary strategies Genetic programming Summary Outline Genetic Progrmming Evolutionry strtegies Genetic progrmming Summry Bsed on the mteril provided y Professor Michel Negnevitsky Evolutionry Strtegies An pproch simulting nturl evolution ws proposed

More information