Implicit Runge-Kutta method for Van der pol problem

Size: px
Start display at page:

Download "Implicit Runge-Kutta method for Van der pol problem"

Transcription

1 Appled d Computtol Mthemts 5; 4(-: - Publshed ole Jul, 4 ( do:.48/.m.s.54. ISSN: 8-55 (Prt; ISSN: 8-5 (Ole Implt Ruge-Kutt method for V der pol problem Jfr Bzr *, Mesm Nvd Deprtmet of Appled Mthemts, Fult of Mthemtl sees, Uverst of Gul, P.O Box: 45-94, Rsht, Ir Emls ddress: fr.bzr@gml.om (J. Bzr, bzr@gul..r (J. Bzr, mvd@gml.om (M. Nvd To te ths rtle: Jfr Bzr, Mesm Nvd. Implt Ruge-Kutt Method for V Der Pol Problem. Appled d Computtol Mthemts. Spel Issue: New orettos Appled d Computtol Mthemts. Vol. 4, No. -, 5, pp. -. do:.48/.m.s.54. Abstrt: I ths musrpt the mplt Ruge-Kutt (IRK method, wth three slopes of order fve hs bee expled, d s ppled to V der pol stff dfferetl equto. Truto error, of order fve, hs bee estmted. Stblt of the proedure for the V der pol equto, s lzed b the Lpuov method. To llustrte the struture of the method, Algorthm s preseted to solve ths stff problem. Results ofrm the vldt d the blt of ths pproh. Kewords: Implt Method, Tlor Seres, Legedre Orthogol Poloml, V Der Pol Equto, Lpuov Futo. Itroduto A Implt Ruge-Kutt method for solvg dfferetl equto = f ( t, wth ν slopes s defed b the followg equto: d Where ν w K = = ν K = hf ( t h, K = = ν =,,..., ν Ad,, ν, w, w,..., w ν re prmeters tht wll be determed. The futo K s K = h f ( t h, K K K, defed b set of ν mplt equto.( see [] d [] = wk wk wk, ( I eletro, the V der Pol oslltor s o- =,,. Where,,, w,, re twelve rbtrr prmeters, whh should be determed. The Tlor seres gves oservtve oslltor wth o-ler dmpg. Ths problem ws orgll trodued b V der pol (9 the stud of eletro rut b the followg seod order stff dfferetl equto u u u u '' ε ( ' =. Where u s futo of the tme t, d ε s postve slr prmeter dtg the olert d the stregth of the dmpg. (see [4] p- & [] p-. The Implt Ruge-Kutt Method I ths mplt method let's ν =, the we hve the followg equto Where 4 v ( t = ( t h ( t h ( t h ( t h ( t... ( 4

2 Appled d Computtol Mthemts 5; 4(-: - 7 ( t = f ( t, ( t = ( f t ff = ( f f = Df t ( t = [( f ff f f f ( f ff ] = D f f Df tt t t t f ff f f f f f f ff f f v ( = [( ttt tt t ( tt t f ff f ff f = D f f D f Df Df f ( t ( t ] Df Bsed o expso of two-vrble futo, the equto K ( hges to: ( These equtos re mplt d we ot esl obt the explt expresso fork, K, d K. I order to determek, K, dk expltl, we ssume the followg form Where A, B, E, D, df re ukow to be determed. Substtutg fork, K, d K from ( 4 to (, d o equtg the terms wth detl powers of h Tlors seres, we obt the followg results: A = f B = f ( A A A f = ( f f f = Df t t E = ( f Df D f D = [ ( ( ( ] f Df ( Df Df ( f D f D f F = [ [( ( ( ( ( f Df Df Df ( fd f D f ] [( ( ( ( ( f Df Df Df (4

3 8 Jfr Bzr d Mesm Nvd: Implt Ruge-Kutt Method for V Der Pol Problem ( fd f D f ] [( ( ( ( f Df Df Df f D f D f f [ (( fdf Df (( fdf Df (( fdf Df ] ft ( fd f ( fttdf ( f ftdf 4 4 f ( fdf D f,, 4 ( ( ]] (5 Numerl method equto ( wth the help of (4 m be wrtte s = h ( w A w A w A h ( w B w B w B h ( w E w E w E h ( w D w D w D... 4 ( Where A, B, E, D, d F re gve b.(5 B equtg the oeffets of the terms wth the detl powers of h ( d (, the followg equtos re obted. whh re the sme s the sstem of equtos Buther trodued ( [] & [] (7 : w = (7 b : w = (7 : w = (7 d : w = 4, = (7 e : w (7 f : w 8, = ( 7 g : w 8, = ( 7 h : w, = ( 7 : w k k =. 4,, k = w,, be determed from (7 7 d, d from (7e 7 d three more the followg equtos,,, =,,, wll be lulted. Buther (94 trodued RK method bsed o the Rdu d Lobtto qudrture formuls. I ths proedure the oeffets re tke the Rdu's roots of the Legedre poloml of degree three: d dx ( ( 4 4 x x = =. The soluto of the sstem (7, fter substtuto of the vlues of results the followg oeffet of Rdu formul of order fve: C W = A = Substtutos of these vlues (, leds to:

4 Appled d Computtol Mthemts 5; 4(-: - 9 (8. Numerl Exmple To llustrte the method, let's ppl IRK o the followg stff problem, whh s kow s V der pol equto: ε '' ( ' =, ( '( =. I the frst step b osderg the ew depedet vrbles, V der pol equto s wrtte, equvletl, s the followg sstem of two frst order dfferetl equto: u u ' = f ( u, v = v ε ( u, u( = v ' g ( u, v u, v ( ε = = = For pplg tertve formul ( 8, to the sstem ( 9 the prmeters K, K should be omputed from the u v IRK_NEWTON ALG( ɛ, step sze h, u, v (9 followg formuls: Ku = hf ( t h, u, Ku, v, Kv Kv = hg ( t h, u, Ku, v, Kv Where,,. The u = u K K K 9 v = v K K K 9 u u u v v v ( Pseudo ode Algorthm: Let's expl the bove method wth followg Pseudo ode of Newto tertve proedure for solvg exmple ( 9 :( tke,, The results of pplg ths lgorthm to the V der pol

5 Jfr Bzr d Mesm Nvd: Implt Ruge-Kutt Method for V Der Pol Problem equto, re plotted for ε =, h =., the followg Fg. must be dded to the omputed qutt order tht the result be extl equl to the qutt tht we re lookg for. Ths mes: ( true omputed qutt T = ( ext soluto The the ext vlue of ( t wll stsf ( t = ( t hϕ ( t, ( t, h T Where ϕ( t, ( t, h s futo of the rgumet t,, d h, d s lled the remet futo, d T s the lol truto error. Let's tke omputed qutt of (8 we get: ( t = t s Fg.. The soluto of Vs der pol equto 4. Truto Error Alss Defto:[] truto error s the qutt T whh f ( t, = t 5 ( t = ( t K K K T t = ( t h = t h( t h h( t h 5 h( t h T T = h 9 The trdtol vlue of the truto error s usull lled Lpuov futo, defed o the set ( osdered s: T = C h ( ζ. omprg wth the S p = { X R : X < P}, d V ( X the the bove vlue of truto error results C =. zero soluto of X = F ( X s stble [9]. 7 Theorem. Let's the postve defte futo So the truto error s of O ( h,.e. the method V ( X exsts s suh V ( X o the ope set Ω, (8 s of order fve. (see [] d [] X = F X, F s futo F : Ω R,M ludes 5. Stblt Alss of the V Der Pol Sstem Defto. Stblt d smptot stblt: The X = F X, s stble, f soluto of sstem of equto s ( for ll t t we get: [9] ε > δ > ( x (t x (t < δ x ( t x ( t < ε ε d the soluto s smptot stble, f t s stble d lso δ > ( x (t x (t < δ x (t x ( t, s t Defto. Ivrt set: A set suh s M R s vrt set of sstem of equto X = F ( X, f from X M olude tht X ( t, X M, for ll t R [9]. Theorem l. If the slr postve defte futo V ( X, ( ll vrt subsets of E λ, where = { : = } d λ = { X R V X λ} E X R V : (. The soluto X ( t, X C λ X = F X, overges to them []. Corollr. Let's the ssumptos of the theorem hold. If zero s ol vrt pot of E, the the zero soluto of X = F ( X s smptotll stble []. of ( Stblt of the sstem of equto (9 s proved the followg: Let's V ( u, v = ( u v, whh s postve defte o R d u V ( u, v = εu (, the o the strp { ( u, v R } : u, v Ω= < < < <, we hve. It s obvous tht for E = {( u, v Ω : u = }, sstem ( 9 s overted to the followg sstem: V ( X

6 Appled d Computtol Mthemts 5; 4(-: - u ' = v v ' = Regrdg the lst orollr the set ludg zero s the ol vrt subset of., s the smptot E Ad ( stble pot of (9. To determe the smptot stblt re, Let's osder the set of urves V ( u, v = λ, where λ, ( u, v Ω. Ths set s obvousl losed d the urves re smmetr wth respet to the u xs. The futo u s deresg o the tervl (, ] d reses o the < u <. For the ostt λ, the urve V ( u, v = λ uts the borders t oe of the pots (, or (,. So the best vlue for the prmeter λ s equl to ( (, d smptot λ = m (, = stblt re ossts of the potes the losed rle C = { ( u, v Ω : u v λ }. The lmt le of the V der pol equto s out of the rle u v = (see [] p-.. Colusos Se there re three dfferet tops studed, oluso s lso dvded dfferet prts; A-From truto error seto, we olude tht order of ths mplt method s fve, d ths mes tht ths umerl method s prese for polomls of degree less th sx. B- The dsdvtge of the Ruge-Kutt methods s tht the volve osderbl more omputtos, but hve the dvtge of self strtg. wth h =. ol used utl C- Method ( ε =, d for ε >, the order of the method should resed or relted step sze deresed. D- From stblt lss seto, we olude tht the method ppled to the V der pol equto s stble, Ad ths mes the formul of the umerl method s sestve to smll hge the lol errors. Referees [] Buther J.C. Numerl Methods for Ordr Dfferetl Equtos. Joh Wle,. [] Frk R, Shed J, Uberhuber C.W: Order results for mplt Ruge-Kutt methods ppled to stff sstems. SIAM J. Numer. Al.,, (985. [] Hrer E, Lubh C, Rohe M: Error of Ruge-Kutt methods for stff problems studed v dfferetl lgebr equtos. BIT 8, 78-7 (988. [4] Hrer E, Lubh C, Rohe M: The Numerl Soluto of Dfferetl-Algebr Sstems b Ruge-Kutt Methods. Sprger verlg (989. [5] Hrer. E, Wer. G & Nørsett S.P. " Solvg Ordr Dfferetl Equtos I, ostff problems ", Sprger Seres Computtol Mthemts 4, DOI.7/ , Sprger-Verlg Berl Hedelberg. [] J M.J. Numerl Soluto of Dfferetl Equtos. Joh Wle & Sos (As Pte Ltd(979. [7] Klm R. E. & Bertrm J. F: "Cotrol Sstem Alss d Desg v the Seod Method of Lpuov", J. Bs Egrgvol.88 9 pp.7; 94. [8] Lefshetz.s. Dfferetl equto: Geometr theor, d edto. Itersee, New York, 9. [9] Lkshmkthm v, Leel s: Dfferetl d tegrl equltes: theor d ppltos, volume I, Alem Press.(99 [] Rm Mh Ro.M. A ote o tegrl eqult, J. Id Mth, So. 7, 7-9, 9. [] Rm Moh Ro.M. Ordr dfferetl equtos : theor d ppltos, Lodo : E. Arold, 98, ISBN :

Diagonally Implicit Runge-Kutta Nystrom General Method Order Five for Solving Second Order IVPs

Diagonally Implicit Runge-Kutta Nystrom General Method Order Five for Solving Second Order IVPs WSEAS TRANSACTIONS o MATHEMATICS Fudzh Isml Dgoll Implt Ruge-Kutt Nstrom Geerl Method Order Fve for Solvg Seod Order IVPs FUDZIAH ISMAIL Deprtmet of Mthemts Uverst Putr Mls Serdg Selgor MALAYSIA fudzh@mth.upm.edu.m

More information

Numerical Analysis Topic 4: Least Squares Curve Fitting

Numerical Analysis Topic 4: Least Squares Curve Fitting Numerl Alss Top 4: Lest Squres Curve Fttg Red Chpter 7 of the tetook Alss_Numerk Motvto Gve set of epermetl dt: 3 5. 5.9 6.3 The reltoshp etwee d m ot e ler. Fd futo f tht est ft the dt 3 Alss_Numerk Motvto

More information

Mathematically, integration is just finding the area under a curve from one point to another. It is b

Mathematically, integration is just finding the area under a curve from one point to another. It is b Numerl Metods or Eg [ENGR 9] [Lyes KADEM 7] CHAPTER VI Numerl Itegrto Tops - Rem sums - Trpezodl rule - Smpso s rule - Rrdso s etrpolto - Guss qudrture rule Mtemtlly, tegrto s just dg te re uder urve rom

More information

Chapter Gauss-Seidel Method

Chapter Gauss-Seidel Method Chpter 04.08 Guss-Sedel Method After redg ths hpter, you should be ble to:. solve set of equtos usg the Guss-Sedel method,. reogze the dvtges d ptflls of the Guss-Sedel method, d. determe uder wht odtos

More information

Numerical Differentiation and Integration

Numerical Differentiation and Integration Numerl Deretto d Itegrto Overvew Numerl Deretto Newto-Cotes Itegrto Formuls Trpezodl rule Smpso s Rules Guss Qudrture Cheyshev s ormul Numerl Deretto Forwrd te dvded deree Bkwrd te dvded deree Ceter te

More information

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM S. Res. Chem. Commu.: (3 8-88 ISSN 77-669 GENERLIZED OPERTIONL RELTIONS ND PROPERTIES OF FRCTIONL NKEL TRNSFORM R. D. TYWDE *. S. GUDDE d V. N. MLLE b Pro. Rm Meghe Isttute o Teholog & Reserh Bder MRVTI

More information

MTH 146 Class 7 Notes

MTH 146 Class 7 Notes 7.7- Approxmte Itegrto Motvto: MTH 46 Clss 7 Notes I secto 7.5 we lered tht some defte tegrls, lke x e dx, cot e wrtte terms of elemetry fuctos. So, good questo to sk would e: How c oe clculte somethg

More information

INTERPOLATION(2) ELM1222 Numerical Analysis. ELM1222 Numerical Analysis Dr Muharrem Mercimek

INTERPOLATION(2) ELM1222 Numerical Analysis. ELM1222 Numerical Analysis Dr Muharrem Mercimek ELM Numerl Alss Dr Murrem Merme INTEROLATION ELM Numerl Alss Some of te otets re dopted from Luree V. Fusett Appled Numerl Alss usg MATLAB. rete Hll I. 999 ELM Numerl Alss Dr Murrem Merme Tod s leture

More information

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS PubH 745: REGRESSION ANALSIS REGRESSION IN MATRIX TERMS A mtr s dspl of umbers or umercl quttes ld out rectgulr rr of rows d colums. The rr, or two-w tble of umbers, could be rectgulr or squre could be

More information

CURVE FITTING LEAST SQUARES METHOD

CURVE FITTING LEAST SQUARES METHOD Nuercl Alss for Egeers Ger Jord Uverst CURVE FITTING Although, the for of fucto represetg phscl sste s kow, the fucto tself ot be kow. Therefore, t s frequetl desred to ft curve to set of dt pots the ssued

More information

Matrix. Definition 1... a1 ... (i) where a. are real numbers. for i 1, 2,, m and j = 1, 2,, n (iii) A is called a square matrix if m n.

Matrix. Definition 1... a1 ... (i) where a. are real numbers. for i 1, 2,, m and j = 1, 2,, n (iii) A is called a square matrix if m n. Mtrx Defto () s lled order of m mtrx, umer of rows ( 橫行 ) umer of olums ( 直列 ) m m m where j re rel umers () B j j for,,, m d j =,,, () s lled squre mtrx f m (v) s lled zero mtrx f (v) s lled detty mtrx

More information

Estimation in Step-Stress Partially Accelerated Life Tests for the Burr Type XII distribution Using Type I Censoring By. Abstract

Estimation in Step-Stress Partially Accelerated Life Tests for the Burr Type XII distribution Using Type I Censoring By. Abstract Estmto Step-Stress Prtll elerted fe Tests for the Burr Tpe XII dstrbuto Usg Tpe I Cesorg B bd-elftth,. M. _ftth@hotml.om ml S. Hss ml5_solm@hoo.om d Nssr, S. G. sdbosd@hoo.om Isttute of Sttstl Studes &

More information

SOLVING INITIAL VALUE PROBLEM USING RUNGE-KUTTA 6 th ORDER METHOD

SOLVING INITIAL VALUE PROBLEM USING RUNGE-KUTTA 6 th ORDER METHOD VOL. NO. JULY ISSN 898 ARPN Jourl o Egeerg d Appled Sees As Reserh Pulshg Networ ARPN. All rghts reserved. www.rpourls.om SOLVING INITIAL VALUE PROBLEM USING RUNGEUTTA th ORDER METHOD As Fdhl As AlShmmr

More information

Chapter Simpson s 1/3 Rule of Integration. ( x)

Chapter Simpson s 1/3 Rule of Integration. ( x) Cpter 7. Smpso s / Rule o Itegrto Ater redg ts pter, you sould e le to. derve te ormul or Smpso s / rule o tegrto,. use Smpso s / rule t to solve tegrls,. develop te ormul or multple-segmet Smpso s / rule

More information

Chapter 12-b Integral Calculus - Extra

Chapter 12-b Integral Calculus - Extra C - Itegrl Clulus Cpter - Itegrl Clulus - Etr Is Newto Toms Smpso BONUS Itroduto to Numerl Itegrto C - Itegrl Clulus Numerl Itegrto Ide s to do tegrl smll prts, lke te wy we preseted tegrto: summto. Numerl

More information

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y 4. Le Itegrls I ths secto we defe tegrl tht s smlr to sgle tegrl except tht sted of tegrtg over tervl [ ] we tegrte over curve. Such tegrls re clled le tegrls lthough curve tegrls would e etter termology.

More information

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini DATA FITTING Itesve Computto 3/4 Als Mss Dt fttg Dt fttg cocers the problem of fttg dscrete dt to obt termedte estmtes. There re two geerl pproches two curve fttg: Iterpolto Dt s ver precse. The strteg

More information

Analele Universităţii din Oradea, Fascicula: Protecţia Mediului, Vol. XIII, 2008

Analele Universităţii din Oradea, Fascicula: Protecţia Mediului, Vol. XIII, 2008 Alele Uverstăţ d Orde Fsul: Proteţ Medulu Vol. XIII 00 THEORETICAL AND COMPARATIVE STUDY REGARDING THE MECHANICS DISPLASCEMENTS UNDER THE STATIC LOADINGS FOR THE SQUARE PLATE MADE BY WOOD REFUSE AND MASSIF

More information

The Z-Transform in DSP Lecture Andreas Spanias

The Z-Transform in DSP Lecture Andreas Spanias The Z-Trsform DSP eture - Adres Ss ss@su.edu 6 Coyrght 6 Adres Ss -- Poles d Zeros of I geerl the trsfer futo s rtol; t hs umertor d deomtor olyoml. The roots of the umertor d deomtor olyomls re lled the

More information

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ]

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ] Are d the Defte Itegrl 1 Are uder Curve We wt to fd the re uder f (x) o [, ] y f (x) x The Prtto We eg y prttog the tervl [, ] to smller su-tervls x 0 x 1 x x - x -1 x 1 The Bsc Ide We the crete rectgles

More information

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ]

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ] Atervtves The Itegrl Atervtves Ojectve: Use efte tegrl otto for tervtves. Use sc tegrto rules to f tervtves. Aother mportt questo clculus s gve ervtve f the fucto tht t cme from. Ths s the process kow

More information

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat

More information

PROBLEM SET #4 SOLUTIONS by Robert A. DiStasio Jr.

PROBLEM SET #4 SOLUTIONS by Robert A. DiStasio Jr. PROBLM ST # SOLUTIONS y Roert. DStso Jr. Q. Prove tht the MP eergy s sze-osstet for two ftely seprted losed shell frgmets. The MP orrelto eergy s gve the sp-ortl ss s: vrt vrt MP orr Δ. or two moleulr

More information

COMPLEX NUMBERS AND DE MOIVRE S THEOREM

COMPLEX NUMBERS AND DE MOIVRE S THEOREM COMPLEX NUMBERS AND DE MOIVRE S THEOREM OBJECTIVE PROBLEMS. s equl to b d. 9 9 b 9 9 d. The mgr prt of s 5 5 b 5. If m, the the lest tegrl vlue of m s b 8 5. The vlue of 5... s f s eve, f s odd b f s eve,

More information

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +.

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +. Ler Trsfortos d Group Represettos Hoework #3 (06-07, Aswers Q-Q re further exerses oer dots, self-dot trsfortos, d utry trsfortos Q3-6 volve roup represettos Of these, Q3 d Q4 should e quk Q5 s espelly

More information

The Algebraic Least Squares Fitting Of Ellipses

The Algebraic Least Squares Fitting Of Ellipses IOSR Jourl of Mthets (IOSR-JM) e-issn: 78-578 -ISSN: 39-765 Volue 4 Issue Ver II (Mr - Ar 8) PP 74-83 wwwosrjourlsorg he Algebr Lest Squres Fttg Of Ellses Abdelltf Betteb Dertet of Geerl Studes Jubl Idustrl

More information

Systems of second order ordinary differential equations

Systems of second order ordinary differential equations Ffth order dgolly mplct Ruge-Kutt Nystrom geerl method solvg secod Order IVPs Fudzh Isml Astrct A dgolly mplct Ruge-Kutt-Nystróm Geerl (SDIRKNG) method of ffth order wth explct frst stge for the tegrto

More information

Available online through

Available online through Avlble ole through wwwmfo FIXED POINTS FOR NON-SELF MAPPINGS ON CONEX ECTOR METRIC SPACES Susht Kumr Moht* Deprtmet of Mthemtcs West Begl Stte Uverst Brst 4 PrgsNorth) Kolt 76 West Begl Id E-ml: smwbes@yhoo

More information

Global Journal of Engineering and Technology Review

Global Journal of Engineering and Technology Review Glol Jourl of Egeerg d eholog Revew Jourl homepge: http://gjetr.org/ Glol Jourl of Egeerg d eholog Revew () 85 9 (06) Applto of Cojugte Grdet Method wth Cu No- Poloml Sple Sheme for Solvg wo-pot Boudr

More information

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions HK Km Slghtly moded //9 /8/6 Frstly wrtte t Mrch 5 Itertve Methods er Systems: Guss-Sedel Noler Systems Cse Study: Chemcl Rectos Itertve or ppromte methods or systems o equtos cosst o guessg vlue d the

More information

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION St Joh s College UPPER V Mthemtcs: Pper Lerg Outcome d ugust 00 Tme: 3 hours Emer: GE Mrks: 50 Modertor: BT / SLS INSTRUCTIONS ND INFORMTION Red the followg structos crefull. Ths questo pper cossts of

More information

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4 // Sples There re ses where polyoml terpolto s d overshoot oslltos Emple l s Iterpolto t -,-,-,-,,,,,.... - - - Ide ehd sples use lower order polyomls to oet susets o dt pots mke oetos etwee djet sples

More information

The linear system. The problem: solve

The linear system. The problem: solve The ler syste The prole: solve Suppose A s vertle, the there ests uue soluto How to effetly opute the soluto uerlly??? A A A evew of dret ethods Guss elto wth pvotg Meory ost: O^ Coputtol ost: O^ C oly

More information

ES240 Solid Mechanics Z. Suo. Principal stress. . Write in the matrix notion, and we have

ES240 Solid Mechanics Z. Suo. Principal stress. . Write in the matrix notion, and we have ES4 Sold Mehs Z Suo Prpl stress Prpl Stress Imge mterl prtle stte o stress The stte o stress s xed, but we represet the mterl prtle my wys by uttg ubes deret orettos For y gve stte o stress, t s lwys possble

More information

under the curve in the first quadrant.

under the curve in the first quadrant. NOTES 5: INTEGRALS Nme: Dte: Perod: LESSON 5. AREAS AND DISTANCES Are uder the curve Are uder f( ), ove the -s, o the dom., Prctce Prolems:. f ( ). Fd the re uder the fucto, ove the - s, etwee,.. f ( )

More information

Stats & Summary

Stats & Summary Stts 443.3 & 85.3 Summr The Woodbur Theorem BCD B C D B D where the verses C C D B, d est. Block Mtrces Let the m mtr m q q m be rttoed to sub-mtrces,,,, Smlrl rtto the m k mtr B B B mk m B B l kl Product

More information

CS473-Algorithms I. Lecture 3. Solving Recurrences. Cevdet Aykanat - Bilkent University Computer Engineering Department

CS473-Algorithms I. Lecture 3. Solving Recurrences. Cevdet Aykanat - Bilkent University Computer Engineering Department CS473-Algorthms I Lecture 3 Solvg Recurreces Cevdet Aykt - Blket Uversty Computer Egeerg Deprtmet Solvg Recurreces The lyss of merge sort Lecture requred us to solve recurrece. Recurreces re lke solvg

More information

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1.

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1. SPECIAL MATRICES SYMMETRIC MATRICES Def: A mtr A s symmetr f d oly f A A, e,, Emple A s symmetr Def: A mtr A s skew symmetr f d oly f A A, e,, Emple A s skew symmetr Remrks: If A s symmetr or skew symmetr,

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 Mtr Trsformtos usg Egevectors September 8, Mtr Trsformtos Usg Egevectors Lrry Cretto Mechcl Egeerg A Semr Egeerg Alyss September 8, Outle Revew lst lecture Trsformtos wth mtr of egevectors: = - A ermt

More information

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases Itertol Jourl of Advced Reserch Physcl Scece (IJARPS) Volume, Issue 5, September 204, PP 6-0 ISSN 2349-7874 (Prt) & ISSN 2349-7882 (Ole) www.rcourls.org Alytcl Approch for the Soluto of Thermodymc Idettes

More information

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n 0. Sere I th ecto, we wll troduce ere tht wll be dcug for the ret of th chpter. Wht ere? If we dd ll term of equece, we get whch clled fte ere ( or jut ere) d deoted, for hort, by the ymbol or Doe t mke

More information

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11:

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11: Soo Kg Lm 1.0 Nested Fctorl Desg... 1.1 Two-Fctor Nested Desg... 1.1.1 Alss of Vrce... Exmple 1... 5 1.1. Stggered Nested Desg for Equlzg Degree of Freedom... 7 1.1. Three-Fctor Nested Desg... 8 1.1..1

More information

On Testing Simple and Composite Goodness-of-Fit Hypotheses When Data are Censored

On Testing Simple and Composite Goodness-of-Fit Hypotheses When Data are Censored ALT`8 Jue 9- Bordeux O Testg mple d Composte Goodess-of-Ft Hypotheses Whe Dt re Cesored 35 EV Chmtov BYu Lemesho Novosbrs tte Tehl Uversty Russ Abstrt Problems of pplto of the oprmetr olmogorov Crmer-vo

More information

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek Optmlt of Strteges for Collpsg Expe Rom Vrles Smple Rom Smple E Stek troucto We revew the propertes of prectors of ler comtos of rom vrles se o rom vrles su-spce of the orgl rom vrles prtculr, we ttempt

More information

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005 Seto 2:00 ~ 2:50 pm Thursday Marylad 202 Sep. 29, 2005. Homework assgmets set ad 2 revews: Set : P. A box otas 3 marbles, red, gree, ad blue. Cosder a expermet that ossts of takg marble from the box, the

More information

5 - Determinants. r r. r r. r r. r s r = + det det det

5 - Determinants. r r. r r. r r. r s r = + det det det 5 - Detemts Assote wth y sque mtx A thee s ume lle the etemt of A eote A o et A. Oe wy to efe the etemt, ths futo fom the set of ll mtes to the set of el umes, s y the followg thee popetes. All mtes elow

More information

Chapter 7. Bounds for weighted sums of Random Variables

Chapter 7. Bounds for weighted sums of Random Variables Chpter 7. Bouds for weghted sums of Rdom Vrbles 7. Itroducto Let d 2 be two depedet rdom vrbles hvg commo dstrbuto fucto. Htczeko (998 d Hu d L (2000 vestgted the Rylegh dstrbuto d obted some results bout

More information

Math 10 Discrete Mathematics

Math 10 Discrete Mathematics Math 0 Dsrete Mathemats T. Heso REVIEW EXERCISES FOR EXM II Whle these problems are represetatve of the types of problems that I mght put o a exam, they are ot lusve. You should be prepared to work ay

More information

Sequences and summations

Sequences and summations Lecture 0 Sequeces d summtos Istructor: Kgl Km CSE) E-ml: kkm0@kokuk.c.kr Tel. : 0-0-9 Room : New Mleum Bldg. 0 Lb : New Egeerg Bldg. 0 All sldes re bsed o CS Dscrete Mthemtcs for Computer Scece course

More information

Analyzing Control Structures

Analyzing Control Structures Aalyzg Cotrol Strutures sequeg P, P : two fragmets of a algo. t, t : the tme they tae the tme requred to ompute P ;P s t t Θmaxt,t For loops for to m do P t: the tme requred to ompute P total tme requred

More information

19 22 Evaluate the integral by interpreting it in terms of areas. (1 x ) dx. y Write the given sum or difference as a single integral in

19 22 Evaluate the integral by interpreting it in terms of areas. (1 x ) dx. y Write the given sum or difference as a single integral in SECTION. THE DEFINITE INTEGRAL. THE DEFINITE INTEGRAL A Clck here for swers. S Clck here for solutos. Use the Mdpot Rule wth the gve vlue of to pproxmte the tegrl. Roud the swer to four decml plces. 9

More information

20 23 Evaluate the integral by interpreting it in terms of areas. (1 x ) dx. y 2 2

20 23 Evaluate the integral by interpreting it in terms of areas. (1 x ) dx. y 2 2 SECTION 5. THE DEFINITE INTEGRAL 5. THE DEFINITE INTEGRAL A Clck here for swers. S Clck here for solutos. 7 Use the Mdpot Rule wth the gve vlue of to pproxmte the tegrl. Roud the swer to four decml plces.

More information

A Mean- maximum Deviation Portfolio Optimization Model

A Mean- maximum Deviation Portfolio Optimization Model A Mea- mamum Devato Portfolo Optmzato Model Wu Jwe Shool of Eoom ad Maagemet, South Cha Normal Uversty Guagzhou 56, Cha Tel: 86-8-99-6 E-mal: wujwe@9om Abstrat The essay maes a thorough ad systemat study

More information

On a class of analytic functions defined by Ruscheweyh derivative

On a class of analytic functions defined by Ruscheweyh derivative Lfe Scece Jourl ;9( http://wwwlfescecestecom O clss of lytc fuctos defed by Ruscheweyh dervtve S N Ml M Arf K I Noor 3 d M Rz Deprtmet of Mthemtcs GC Uversty Fslbd Pujb Pst Deprtmet of Mthemtcs Abdul Wl

More information

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is Mth Sprg 08 L Approxmtg Dete Itegrls I Itroducto We hve studed severl methods tht llow us to d the exct vlues o dete tegrls However, there re some cses whch t s ot possle to evlute dete tegrl exctly I

More information

SOLUTION OF TWO DIMENSIONAL FRACTIONAL ORDER VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS

SOLUTION OF TWO DIMENSIONAL FRACTIONAL ORDER VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS Jourl of Al-Nhr Uversty Vol. (4), Deeber, 009,.85-89 See SOLUTION OF TWO DIMENSIONAL FRACTIONAL ORDER VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS Mh A. Mohed * d Fdhel S. Fdhel ** * Dertet of Mthets, Ib-Al-Hth

More information

PAIR OF STRAIGHT LINES. will satisfy L1 L2 0, and thus L1 L. 0 represent? It is obvious that any point lying on L 1

PAIR OF STRAIGHT LINES. will satisfy L1 L2 0, and thus L1 L. 0 represent? It is obvious that any point lying on L 1 LOCUS 33 Seto - 3 PAIR OF STRAIGHT LINES Cosder two les L L Wht do ou thk wll L L represet? It s ovous tht pot lg o L d L wll stsf L L, d thus L L represets the set of pots osttutg oth the les,.e., L L

More information

Chapter 1 Counting Methods

Chapter 1 Counting Methods AlbertLudwgs Uversty Freburg Isttute of Empral Researh ad Eoometrs Dr. Sevtap Kestel Mathematal Statsts - Wter 2008 Chapter Coutg Methods Am s to determe how may dfferet possbltes there are a gve stuato.

More information

Module 2: Introduction to Numerical Analysis

Module 2: Introduction to Numerical Analysis CY00 Itroducto to Computtol Chemtr Autum 00-0 Module : Itroducto to umercl Al Am of the preet module. Itroducto to c umercl l. Developg mple progrm to mplemet the umercl method opc of teret. Iterpolto:

More information

Computer Programming

Computer Programming Computer Progrmmg I progrmmg, t s ot eough to be vetve d geous. Oe lso eeds to be dscpled d cotrolled order ot be become etgled oe's ow completes. Hrl D. Mlls, Forwrd to Progrmmg Proverbs b Her F. Ledgrd

More information

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl Alyss for Egeers Germ Jord Uversty ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl soluto of lrge systems of ler lgerc equtos usg drect methods such s Mtr Iverse, Guss

More information

Chapter Linear Regression

Chapter Linear Regression Chpte 6.3 Le Regesso Afte edg ths chpte, ou should be ble to. defe egesso,. use sevel mmzg of esdul cte to choose the ght cteo, 3. deve the costts of le egesso model bsed o lest sques method cteo,. use

More information

CHAPTER 5 Vectors and Vector Space

CHAPTER 5 Vectors and Vector Space HAPTE 5 Vetors d Vetor Spe 5. Alger d eometry of Vetors. Vetor A ordered trple,,, where,, re rel umers. Symol:, B,, A mgtude d dreto.. Norm of vetor,, Norm =,, = = mgtude. Slr multplto Produt of slr d

More information

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process

Ruin Probability-Based Initial Capital of the Discrete-Time Surplus Process Ru Probablty-Based Ital Captal of the Dsrete-Tme Surplus Proess by Parote Sattayatham, Kat Sagaroo, ad Wathar Klogdee AbSTRACT Ths paper studes a surae model uder the regulato that the surae ompay has

More information

Numerical Methods. Lecture 5. Numerical integration. dr hab. inż. Katarzyna Zakrzewska, prof. AGH. Numerical Methods lecture 5 1

Numerical Methods. Lecture 5. Numerical integration. dr hab. inż. Katarzyna Zakrzewska, prof. AGH. Numerical Methods lecture 5 1 Numeril Methods Leture 5. Numeril itegrtio dr h. iż. Ktrzy Zkrzewsk, pro. AGH Numeril Methods leture 5 Outlie Trpezoidl rule Multi-segmet trpezoidl rule Rihrdso etrpoltio Romerg's method Simpso's rule

More information

On Several Inequalities Deduced Using a Power Series Approach

On Several Inequalities Deduced Using a Power Series Approach It J Cotemp Mth Sceces, Vol 8, 203, o 8, 855-864 HIKARI Ltd, wwwm-hrcom http://dxdoorg/02988/jcms2033896 O Severl Iequltes Deduced Usg Power Seres Approch Lored Curdru Deprtmet of Mthemtcs Poltehc Uversty

More information

The formulae in this booklet have been arranged according to the unit in which they are first

The formulae in this booklet have been arranged according to the unit in which they are first Fomule Booklet Fomule Booklet The fomule ths ooklet hve ee ge og to the ut whh the e fst toue. Thus te sttg ut m e eque to use the fomule tht wee toue peeg ut e.g. tes sttg C mght e epete to use fomule

More information

Preliminary Examinations: Upper V Mathematics Paper 1

Preliminary Examinations: Upper V Mathematics Paper 1 relmr Emtos: Upper V Mthemtcs per Jul 03 Emer: G Evs Tme: 3 hrs Modertor: D Grgortos Mrks: 50 INSTRUCTIONS ND INFORMTION Ths questo pper sts of 0 pges, cludg swer Sheet pge 8 d Iformto Sheet pges 9 d 0

More information

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES Avlble ole t http://sc.org J. Mth. Comput. Sc. 4 (04) No. 05-7 ISSN: 97-507 SUM PROPERTIES OR THE K-UCAS NUMBERS WITH ARITHMETIC INDEXES BIJENDRA SINGH POOJA BHADOURIA AND OMPRAKASH SIKHWA * School of

More information

The definite Riemann integral

The definite Riemann integral Roberto s Notes o Itegrl Clculus Chpter 4: Defte tegrls d the FTC Secto 4 The defte Rem tegrl Wht you eed to kow lredy: How to ppromte the re uder curve by usg Rem sums. Wht you c ler here: How to use

More information

Chapter 1 Vector Spaces

Chapter 1 Vector Spaces Chpter Vetor pes - Vetor pes Ler Comtos Vetor spe V V s set over fel F f V F! + V. Eg. R s vetor spe. For R we hek -4=-4-4R -7=-7-7R et. Eg. how tht the set of ll polomls PF wth oeffets from F s vetor

More information

On the Nonlinear Difference Equation

On the Nonlinear Difference Equation Joural of Appled Mathemats ad Phss 6 4-9 Pulshed Ole Jauar 6 SRes http://wwwsrporg/joural/jamp http://ddoorg/436/jamp644 O the Nolear Dfferee Equato Elmetwall M Elaas Adulmuhaem A El-Bat Departmet of Mathemats

More information

Lecture 3: Review of Linear Algebra and MATLAB

Lecture 3: Review of Linear Algebra and MATLAB eture 3: Revew of er Aler AAB Vetor mtr otto Vetors tres Vetor spes er trsformtos Eevlues eevetors AAB prmer Itrouto to Ptter Reoto Rro Guterrez-su Wrht Stte Uverst Vetor mtr otto A -mesol (olum) vetor

More information

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector evel-2 BS trx-vector opertos wth 2 opertos sequetlly BS-Notto: S --- sgle precso G E geerl mtrx V --- vector defes SGEV, mtrx-vector product: r y r α x β r y ther evel-2 BS: Solvg trgulr system x wth trgulr

More information

Describes techniques to fit curves (curve fitting) to discrete data to obtain intermediate estimates.

Describes techniques to fit curves (curve fitting) to discrete data to obtain intermediate estimates. CURVE FITTING Descbes techques to ft cuves (cuve fttg) to dscete dt to obt temedte estmtes. Thee e two geel ppoches fo cuve fttg: Regesso: Dt ehbt sgfct degee of sctte. The stteg s to deve sgle cuve tht

More information

Chapter 17. Least Square Regression

Chapter 17. Least Square Regression The Islmc Uvest of Gz Fcult of Egeeg Cvl Egeeg Deptmet Numecl Alss ECIV 336 Chpte 7 Lest que Regesso Assocte Pof. Mze Abultef Cvl Egeeg Deptmet, The Islmc Uvest of Gz Pt 5 - CURVE FITTING Descbes techques

More information

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table.

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table. CURVE FITTING Obectve curve ttg s t represet set dscrete dt b uct curve. Csder set dscrete dt s gve tble. 3 3 = T use the dt eectvel, curve epress s tted t the gve dt set, s = + = + + = e b ler uct plml

More information

Chapter 2 Intro to Math Techniques for Quantum Mechanics

Chapter 2 Intro to Math Techniques for Quantum Mechanics Wter 3 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...

More information

The z-transform. LTI System description. Prof. Siripong Potisuk

The z-transform. LTI System description. Prof. Siripong Potisuk The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put

More information

Dynamics of Marine Biological Resources * * * REVIEW OF SOME MATHEMATICS * * *

Dynamics of Marine Biological Resources * * * REVIEW OF SOME MATHEMATICS * * * Dmis o Mrie Biologil Resores A FUNCTION * * * REVIEW OF SOME MATHEMATICS * * * z () z g(,) A tio is rle or orml whih estlishes reltioshi etwee deedet vrile (z) d oe or more ideedet vriles (,) sh tht there

More information

CHAPTER 7 SOLVING FUZZY LINEAR FRACTIONAL PROGRAMMING PROBLEM BY USING TAYLOR'S SERIES METHOD

CHAPTER 7 SOLVING FUZZY LINEAR FRACTIONAL PROGRAMMING PROBLEM BY USING TAYLOR'S SERIES METHOD 67 CHAPTER 7 SOLVING FUZZY LINEAR FRACTIONAL PROGRAMMING PROBLEM BY USING TAYLOR'S SERIES METHOD 7. INTRODUCTION The eso mers the setors le fl ororte lg routo lg mretg me seleto uversty lg stuet mssos

More information

Some Unbiased Classes of Estimators of Finite Population Mean

Some Unbiased Classes of Estimators of Finite Population Mean Itertol Jourl O Mtemtcs Ad ttstcs Iveto (IJMI) E-IN: 3 4767 P-IN: 3-4759 Www.Ijms.Org Volume Issue 09 etember. 04 PP-3-37 ome Ubsed lsses o Estmtors o Fte Poulto Me Prvee Kumr Msr d s Bus. Dertmet o ttstcs,

More information

Solutions Manual for Polymer Science and Technology Third Edition

Solutions Manual for Polymer Science and Technology Third Edition Solutos ul for Polymer Scece d Techology Thrd Edto Joel R. Fred Uer Sddle Rver, NJ Bosto Idols S Frcsco New York Toroto otrel Lodo uch Prs drd Cetow Sydey Tokyo Sgore exco Cty Ths text s ssocted wth Fred/Polymer

More information

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University Advced Algorthmc Prolem Solvg Le Arthmetc Fredrk Hetz Dept of Computer d Iformto Scece Lköpg Uversty Overvew Arthmetc Iteger multplcto Krtsu s lgorthm Multplcto of polyomls Fst Fourer Trsform Systems of

More information

Lecture 3-4 Solutions of System of Linear Equations

Lecture 3-4 Solutions of System of Linear Equations Lecture - Solutos of System of Ler Equtos Numerc Ler Alger Revew of vectorsd mtrces System of Ler Equtos Guss Elmto (drect solver) LU Decomposto Guss-Sedel method (tertve solver) VECTORS,,, colum vector

More information

Problem Set 4 Solutions

Problem Set 4 Solutions 4 Eoom Altos of Gme Theory TA: Youg wg /08/0 - Ato se: A A { B, } S Prolem Set 4 Solutos - Tye Se: T { α }, T { β, β} Se Plyer hs o rte formto, we model ths so tht her tye tke oly oe lue Plyer kows tht

More information

Integration by Parts for D K

Integration by Parts for D K Itertol OPEN ACCESS Jourl Of Moder Egeerg Reserc IJMER Itegrto y Prts for D K Itegrl T K Gr, S Ry 2 Deprtmet of Mtemtcs, Rgutpur College, Rgutpur-72333, Purul, West Begl, Id 2 Deprtmet of Mtemtcs, Ss Bv,

More information

A Novel Composite-rotating Consensus for Multi-agent System

A Novel Composite-rotating Consensus for Multi-agent System d Itertol Symposum o Computer, Commuto, Cotrol d Automto (CA ) A Novel Composte-rottg Cosesus for Mult-get System Gu L Shool of Aerouts d Astrouts Uversty of Eletro See d ehology of Ch ChegDu, Ch lgu@uestedu

More information

Roberto s Notes on Integral Calculus Chapter 4: Definite integrals and the FTC Section 2. Riemann sums

Roberto s Notes on Integral Calculus Chapter 4: Definite integrals and the FTC Section 2. Riemann sums Roerto s Notes o Itegrl Clculus Chpter 4: Defte tegrls d the FTC Secto 2 Rem sums Wht you eed to kow lredy: The defto of re for rectgle. Rememer tht our curret prolem s how to compute the re of ple rego

More information

Recent Progresses on the Simplex Method

Recent Progresses on the Simplex Method Reet Progresses o the Smple Method www.stford.edu/~yyye K.T. L Professor of Egeerg Stford Uversty d Itertol Ceter of Mgemet See d Egeerg Ng Uversty Outles Ler Progrmmg (LP) d the Smple Method Mrkov Deso

More information

Riemann Integral Oct 31, such that

Riemann Integral Oct 31, such that Riem Itegrl Ot 31, 2007 Itegrtio of Step Futios A prtitio P of [, ] is olletio {x k } k=0 suh tht = x 0 < x 1 < < x 1 < x =. More suitly, prtitio is fiite suset of [, ] otiig d. It is helpful to thik of

More information

Maximum Likelihood Estimation

Maximum Likelihood Estimation Marquette Uverst Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Coprght 08 b Marquette Uverst Maxmum Lkelhood Estmato We have bee sag that ~

More information

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION Malasa Joural of Mathematcal Sceces (): 95-05 (00) Fourth Order Four-Stage Dagoall Implct Ruge-Kutta Method for Lear Ordar Dfferetal Equatos Nur Izzat Che Jawas, Fudzah Ismal, Mohamed Sulema, 3 Azm Jaafar

More information

Modeling uncertainty using probabilities

Modeling uncertainty using probabilities S 1571 Itroduto to I Leture 23 Modelg uertty usg probbltes Mlos Huskreht mlos@s.ptt.edu 5329 Seott Squre dmstrto Fl exm: Deember 11 2006 12:00-1:50pm 5129 Seott Squre Uertty To mke dgost feree possble

More information

Design maintenanceand reliability of engineering systems: a probability based approach

Design maintenanceand reliability of engineering systems: a probability based approach Desg mateaead relablty of egeerg systems: a probablty based approah CHPTER 2. BSIC SET THEORY 2.1 Bas deftos Sets are the bass o whh moder probablty theory s defed. set s a well-defed olleto of objets.

More information

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares Itertol Jourl of Scetfc d Reserch Publctos, Volume, Issue, My 0 ISSN 0- A Techque for Costructg Odd-order Mgc Squres Usg Bsc Lt Squres Tomb I. Deprtmet of Mthemtcs, Mpur Uversty, Imphl, Mpur (INDIA) tombrom@gml.com

More information

VECTORS VECTORS VECTORS VECTORS. 2. Vector Representation. 1. Definition. 3. Types of Vectors. 5. Vector Operations I. 4. Equal and Opposite Vectors

VECTORS VECTORS VECTORS VECTORS. 2. Vector Representation. 1. Definition. 3. Types of Vectors. 5. Vector Operations I. 4. Equal and Opposite Vectors 1. Defnton A vetor s n entt tht m represent phsl quntt tht hs mgntude nd dreton s opposed to slr tht ls dreton.. Vetor Representton A vetor n e represented grphll n rrow. The length of the rrow s the mgntude

More information

Chapter Unary Matrix Operations

Chapter Unary Matrix Operations Chpter 04.04 Ury trx Opertos After redg ths chpter, you should be ble to:. kow wht ury opertos mes,. fd the trspose of squre mtrx d t s reltoshp to symmetrc mtrces,. fd the trce of mtrx, d 4. fd the ermt

More information

Review of Linear Algebra

Review of Linear Algebra PGE 30: Forulto d Soluto Geosstes Egeerg Dr. Blhoff Sprg 0 Revew of Ler Alger Chpter 7 of Nuercl Methods wth MATLAB, Gerld Recktewld Vector s ordered set of rel (or cople) uers rrged s row or colu sclr

More information

A Damped Guass-Newton Method for the Generalized Linear Complementarity Problem

A Damped Guass-Newton Method for the Generalized Linear Complementarity Problem Itertol Jourl of Comuter d Iformto Techology (ISSN: 79 764 olume Issue 4 July 3 A Dmed Guss-Newto Method for the Geerlzed Ler Comlemetrty Problem Huju L Houchu Zhou Dertmet of Mthemtcs Ly Uversty L Shdog

More information