[Nachlass] of the Theory of the Arithmetic-Geometric Mean and the Modulus Function.

Size: px
Start display at page:

Download "[Nachlass] of the Theory of the Arithmetic-Geometric Mean and the Modulus Function."

Transcription

1 [Nchlss] of he Theory of he Arihmeic-Geomeric Me d he Modulus Fucio Defiiio d Covergece of he Algorihm [III 6] Le d e wo posiive rel mgiudes d le From hem we form he wo sequeces: i such wy h y wo correspodig erms re he mes of he wo precedig d i fc he erms of he upper series re o e he rihmeic me he lower he geomeric me ie v v We presuppose h squre roos will ll e e s posiive [wih posiive sigs]; he he series coiues idefiiely ll is erms re eirely deermied d hve posiive rel vlues Furher from his direcly follows: If ll erms of he wo series re However if he i follows he iequliy: < d similrly < < K h is ech erms of he lower series is smller he he correspodig erm of he upper series < > < > K Th is he upper series coiully decreses he upper icreses; hece i ecomes cler h oh series hve limiig vlue d respecively which lie ewee d

2 From he relioship/depedecy [Beziehug] follows Similrly < < < < v v < v Th is he mgiudes form cosly descedig series wih he limiig vlue Thus Th is he upper d lower series hve he sme limi d his is smller h ll erms of he firs series u greer h ll he erms of he secod We deoe his limi he Arihmeic-Geomeric Me gm ewee d d wrie M foooe Bcwrds eesio [Rücwärsverlägerug] of he Algorihm we will ow eed he lgorihm cwrds For h purpose we oe h he roos of he qudric equio re rel d posiive s resul of he precodiio d h is he rihmeic he geomeric me ewee oh hese roos Thus we se c c c so h - is o idice/sigify h erm of he upper series which precedes he erm d - s h erm precedig of he lower series; hrough - - he lgorihm hs hus ee eeded cwrds We ow similrly se 6 c ; c c c ; c c

3 c ; c c c e regrded s he coiuio of he upper series o he lef d similrly s he correspodig eesio of he lower series so h ow wo series re hus oied which re coiued [forsez] o oh sides d ifiium: 7 All erms re rel d posiive [d] ech erm of he upper series is greer h he correspodig erms of he lower The firs series decreses from lef o righ he secod ehves ecly opposie [gerde ugeehr-direcly flipped roud] O he righ oh series hve he sme limi u o he lef he upper grows ps ll limis d he lower srys owrds zero ecep whe Th is c c > > c c > c c c > 6c from which i is cler h he series c c c cd ccordigly lso mus overshoo/eceed ech limi Furher < < lim v> < ie he limi vlue of he series is zero From which is see h he series grdully pproches geomeric progressio wih he quoie From he defiiio of he gm is he followig proposiio/heorem so evide h i eeds o furher elucidio: The gm ewee y wo correspodig erms of he upper d lower series 7 is he sme s h ewee d ie 8 lim lim M M M > > Moreover he ruh of he followig relios is immediely relized M M ; 9 M M M M

4 A umericl emple is see s o how fs he lgorihm coverges owrd he limi vlue For emple wih he clculio of M he erms d firs differ i he h deciml plce d d i he erd plce; is lredy smller h More progressio of he lgorihm Ideiies I he sme wy we ow form he lgorihm which leds o Mc d hus se c c c c c c c c c whose correspodig cwrds eesio we oi from he formuls : c c c c c c d i pplies for ll relioships lim lim c M c M c M c i epsio of he relioships 6 d we se geerlly c c c vlid for ll posiive d egive v d ideify c c c The simple relios eis ewee ll hese mgiudes Firs of ll c ; c c d his formul ideed followig 6 lso pplies for egive v Moreover his ecomes c c c c c c c c < c c c

5 c c Furhermore from follows 6 c c c c c c The ls formul is ideicl wih 6 for egive v Correspodig relios pply for he lgorihm ledig o Mc mely: c c c c ; c ; 7 c c < c i follow hus from 7 d c 9 c c furher from d 6 rises c c c c c c c c c c c ; > from 8 is oied i he sme mer hus h ; ; > c c

6 c c he ggrege of d gives: ; ; c c Lsly we oe y sill oe more relio which is ewee he squre roo composed of he elemes of he sme lgorihm: c ; hus rises he formuls c d logously c c Boh relios 8 d c hus e epded i he followig wy: lim lim lim lim M M M M M ; c 6 lim lim c lim lim M c M c M c M c M c Trigoomeric Cosrucio/Delieio/Demosrio/Digrm of he Algorihm [X ] A rigoomeric epressio of he lgorihm of he gm c e give which is usully mos suile for clculio We se: 7 cos M cos M cos M he:

7 cos M cos M cos M cos M Bewee M M M eis esily ssigle relios mely 8 M si M M si M M si M Thus re successively clculed wih he followig Schem: cos M cos M 9 si M M cos M cos M si M M cos M cos M The he gm is direcly give hrough M cos M cos M cos M cos M The Power Series for M [III 6] We posi ow he prolem o fid for he me M series uil o he [forschreiede] powers of Sice[d] M we pply: M Where re cos coefficies; heir deermiio crried ou hrough he fuciol equio sprug from 8 M M We se mely: he from follows M M hus

8 8 8 From which hrough gherig lie coefficies he followig equios for rise: d from h is cquired: Thus he sough series 9 6 M Sice however heir coefficies dhere o o cler lw we igore his series d dop oher wy h wrrs forue oucome 6 The Power Series for M d M [III66-69] We solve he prolem M hrough he power series uil o M M Ad hece he sough series is oied from i which is susiued for ; hrough which rises: M ± d from here: M The coefficies of his series c lso e eslished/cquired/deermied idepedely of i he followig wy I is sid:

9 The M M M M We dd o o his: 6 8 M β β β β --i is immediely oied which due o he ivrice of M compred o/cross from/opposed o/ of permuio of wih- he odd powers of c o occur-- Thus will: 6 β β β K 8 6 β β β β From which hrough he equios of he coefficies follows: β β 6β β β 8β 6β 96β β 6β β β d from here oi: β β β β 6 6 hus we gi come c o he series Ii his series s well he coefficies re sujec o o sigle lw; o he oher hd divide i io oe d ge: K M K where he coefficies hus progress followig very simple lw However his mehod y mes of which we cquired his quie ice resul depeds solely o he uheiciy/coclusiveess[beweisrf] of coclusio y iducio; he deducive proof is he ojecive of he followig cosiderio We me he proposiio: M The fuciol equio he ecomes:

10 M M hus 6 8 i is however i geerl: λ λ! λ λ λ λ λ λ λ ; Thus ecomes: From his follows wo differe clsses of equios for he deermiio of h is 6 Ou of his is oied he relios: } {

11 The preheicl epressio simplifies hrough he ideiy: hus is foud: ±K 6 6 K i pplies however/hus furher wihi: d hus y: 6 ±

12 6 ± ± ± 9 6 ± ± This equio pplies for eve d odd if he wih eve ide re se equl o zero[?] Ou of i follows for successively he relios: wherefrom is oied: 6 9 ' K K ; hrough his is he suspeced lw of coefficies of he series is i fc deomosred 7 The Differeil Equio [III7] The jus ied cocise series sufices s simple s well s eleg differeil equio which is for he eire heory of ereme imporce [eischeideder Bedeuug] We se for he mome: K 6 9 y M K 6 9 so:

13 dy d d y d d y d dy d 9 9K K K 6K K 9K 6K 9 9K 6K K K K d y dy 9 9 y K d d 6 9K K 6K he he ideiy is: Thus is recogized he eisece of he Relio: d y dy d y dy y d d d d Th is y sisfies he Differeil equio d y dy 7 y d d Oher h M hese differeil equios hve furher priculr/idividul [priculeres] iegrl They evidely/pprely remi uchged whe is replced wih For we se ξ So dy ξ dy d y ξ d y dy d ξ dξ d ξ dξ ξ dξ hus d y d - y d dy d y dy ξ ξ ξ ξy ξ dξ dξ Th is 7 urs io

14 y d dy d y d ξ ξ ξ ξ ξ ξ Now M M y is soluio from 7 we oi hus wice/douly priculr [priculeres] iegrl M M M ξ ξ ξ η Ds llgemeie 8 M c M c 8 The complee Ellipicl Iegrl of he firs clss As is geerlly ow hese relios hold φ φ cos d cos φ φ d cos φ φ d K K Thece 9 φ φ cos d φ φ φ φ d 6 6 cos 6 cos cos K K 6 6 M M We hve hus he reciprocl vlue of he gm used i comiio/coecio wih he complee ellipicl iegrl if he firs id 6 Nurlly his mehod/operio c lso del wih iegrls of geerl form For emple if > γ he iegrl ϕ γ β ϕ β ϕ ϕ γ β cos cos d d γ β β β γ β M M

15 Thus he sme reciprocl gm from he reciprocl mimum d miimum of he iegrls [Iegrde] I his form he formul c lso e ssiged/crried ou i he cse h γ < Th is we se ψ ϕ so d ϕ β γ ϕ cos dψ β γ γ cos ψ Also filly/eveully/lsly β β γ M γ d ϕ dψ ψ ϕ β γ cosϕ β γ γ cos ψ β γ β γ d ψ M β γ γ cos ψ Oe recogizes from his h he vlue of complee ellipicl iegrl hs o e evlued y he followig rule: mimum d miimum vlue υ d υ ' of he iegrls i he iervl of iegrio re eslished he he vlue of he iegrl is equl o M υ υ' From his i ecomes cler h if more epressios of he form i he β γ cosϕ iegrl re [Iegriosgeie] hve equl erem heir complee iegrls come o he sme vlue The solved[geloese] prolem c e geerlized i which o s he vlue of he udermied ellipicl iegrl ϕ cos ϕ I would e dvgeous o proceed such h h he iegrd wih he cosies of muliple ϕ is developed: cos P ϕ P cos ϕ P Where P deped oly o The dϕ cos ϕ P cos6ϕ ϕ dϕ cos ϕ

16 P P si ϕ P si ϕ P si 6ϕ Ad sill hus ied oly from he deermiio of P The firs coefficie we lredy ow: P ϕ dϕ M cos ϕ For he deermiio of oher coefficies we will ler give simple mehod d similrly geerlized proof of his phrse [Seze] which is cquired from my url[ursprueglichere] priciples 7 There re lwys people h do o ow of he sulimiy of he eerl ruhs d heir divie euy d herefore hve oly lered o pprecie he vlue of mhemicl ivesigios from heir ppliciliy i he field of pplied sciece; he ove devoeme will hve he use o me hese people more plesed our ivesigio I fc i is geerlly ow of how gre uiliy such rpidly coverge epsio/progressio s h developed from he ove seeces is i physicl sroomy or he heory of plery perurios The coherece/comiio/coecio wih he Ellipse qudr A ellipse is preseed wih semi es > ; he legh of ellipse qur is o e q We he deoe c 67 ; ' ' The s is geerlly ow q is educile hrough complee ellipse iegrl of wo clsses: q d 68 d K d i geerl K d * K we fid for q he series epsio 8 * q * [X 78] 6 K 6 K ;

17 Similrly s he iegrl of he firs clss c lso epress his Iegrl of wo clsses i simple mer hrough he gm We geere mely followig M ' M K K K K s is d M ' M ' d K K d { M ' M ' } d K K wih which follows from 69 he relio d 7 q { M ' M ' } d ie he sough equio We c give i coveie form for clculio From 67 is ' 7 d d ' hus oi d dm ' M ' M ' d ' d ' dm ' q M ' ' M ' d' d he from 66 is dm ' M ' K d' ' Filly we cquire q M ' 7 [X78] K The formul 7 is he so clled Klsseeziehug ewee he complee ellipicl iegrl of firs d secod id 9

18 Cosrucio of he coiuous frcio [X ] The eire ivesigio of he precedig prgrphs ws sed upo he lysis of cse I which we hd ccomplished hrough lysis[zerleug] of he susiuio S i he produc of S m There is however sill oe oher cio/procedure/operio o complee his cse i which ' is developed i coiuous frcio For h we wrie: βi ' γi δ γi δ βi If is sill o e deermied whole umer he we se: γ γ ; δ δ β he ' γ δi i i β I is see immediely h he [followig] cogrueces pply: γ γ mod δ δ mod d h he deermie of he ls frcio is: βγ δ δ βγ We deermie he umer such h δ < β We ow se logously: γ ; β β δ he will e γ δi i β i β i β i γ δi γ i δi where mod β β mod δ βγ δ βγ We choose he whole umer so h 7 β < δ < β I is he hus comied/cosolided ' i βi i γ i δ

19 where he ls frcio iself sisfies covergece d deermi codiios s h from which we hs proceeded Oly wih his frcio c we liewise proceed d oi wih proprie choice he whole umers βi γ i δ i β i i γ i δ mod β γ mod δ mod δ β γ < δ β β < Through coiuio of he procedure eveully frcio for he β hus δ is oied which hus hs he form: γ γ i i Therefore ech susiuio ' c e represeed i he form of coiuous frcio βi 7 ' γi δ i i O i Where he forms odd [ugerde] umer/quiy of rel whole umers Also iversely ech coiuous frcio of he form 7 represes rsformio of he s clss The e is i i i i i i furher susiuio wih he sme properies d hece from he ierio of his coclusio rises he fc h ech coiuous frcio of he form 7 represes susiuio of he s clss wih he deermi By mes of he represeio 7 i is ow esy o emie he ehvior of p q r wih he susiuio i i ; Ki ;

20 he followig 6 8: ' p ' p p K K p p ' p p K K K i q r ' q r K K i K r which compleely correspods wih our formul 6 Oe c ow lwys furher discuss how o cover he ove i coecio o he formul 76 however we will o go io his more sice i is he siclly he sme ri of hough The Qudric Form The Fudmel [ereich] re/divisio/field/rge/scope/domi There remis impor relio ewee he heory of he here reed lier frciol susiuio d h he qudric forms wih egive deermi If F d F re wo qudric forms i he vriles u v d u v wih whole umer coefficies: 77 F u uυ cυ F ' ' u' ' u' υ' c' υ' The oh forms ecome he oher hrough whole umer susiuio of he vrile wih deermi hus oh he forms re clled irisiclly equivele u' u βυ υ ' γu δυ δ βγ A eccesry codiio for he equivelece of wo forms is evidely he equliy of is deermis: d c d' ' c' Oe qudric form F is clled defiie if i lwys hs he sme sig oher h for uv for ll possile rel vlues of u v h is if is roos re o rel he is demi is egive If ow F d F re wo posiive defiie equivele forms h is > '> d d'< u u' From which lso follows c> c >; he mus ewee he vlues d for υ υ' vishig of F d F o follow of he equivelece defiiio relio of he form: u β u' υ υ' u γ δ υ Wih whole rel β γ δ he deermi remis We will hece deoe wo defiie qudric forms of oe vrile:

21 c d ' ' c' As equivele if he roos he oe i d i he oher reled hrough rel lier reciol rel umer susiuio wih he deermi h is if i β ' i γ i δ ' or βi ' γ i δ Thus d rele hrough susiuio of he form Now is y riol vlue λ µ i σi τ Where γ µ σ τ re whole rel umers d umeror d deomior wihou commo fcors The quric form c e foud whose roo is i; h is se: σ τ A λσ µτ B λ µ C AC B λτ µσ D The: σi τ λi µ B Di 8 i σ τ A A roo of he posiive defiie form 8 A B C A B C Which he egive deermie B AC D eiis A equivele form c o his oe 8 c ow lwys e foud for 8 c This form is deoed s he reduced of he origil or lso s he simples equivele form o 8 To rrive his reduced form we proceed wih he followig Algorihm We se 8 D B AA B B ha h whole umer The A C d B we chose s he solue les remider of B mod A hus he h B A Evidely ow D B D B mod A ; We hus se D B A A Ad if o lredy A A will deermie B from he equio B B h A h whole umer Furher will s solue smlles remider of B mod A so h B A

22 The furher is Ad i ecomes If o A A D B mod A D B he furher deermie from B B h A A A h whole umer B s solue smlles remider of B mod A hus B A Ad coiue so forh from D B A A Arises A A wh mus A B A K B Di i A D ib iha A hi hi A D Bi hi h i A B A B A A I ' I ' h g h g g g ' σ : ' σ : ' i σ : ' σ : ' σ : ' σ 6 : ' i i i I I

23 ' K K τ τ τ τ τ τ e e e e q p p q ; ' ' p q p p r p q ' K m K τ τ τ τ e e e e ' cos A p q

24

25

26 Ellipicl iegrl ifiie umer of vlues of he gm Lemisce fucio 9 rsformio of he ellipicl iegrl du/r of ellipse J iegrl of ellipse

LOCUS 1. Definite Integration CONCEPT NOTES. 01. Basic Properties. 02. More Properties. 03. Integration as Limit of a Sum

LOCUS 1. Definite Integration CONCEPT NOTES. 01. Basic Properties. 02. More Properties. 03. Integration as Limit of a Sum LOCUS Defiie egrio CONCEPT NOTES. Bsic Properies. More Properies. egrio s Limi of Sum LOCUS Defiie egrio As eplied i he chper iled egrio Bsics, he fudmel heorem of clculus ells us h o evlue he re uder

More information

Supplement: Gauss-Jordan Reduction

Supplement: Gauss-Jordan Reduction Suppleme: Guss-Jord Reducio. Coefficie mri d ugmeed mri: The coefficie mri derived from sysem of lier equios m m m m is m m m A O d he ugmeed mri derived from he ove sysem of lier equios is [ ] m m m m

More information

Week 8 Lecture 3: Problems 49, 50 Fourier analysis Courseware pp (don t look at French very confusing look in the Courseware instead)

Week 8 Lecture 3: Problems 49, 50 Fourier analysis Courseware pp (don t look at French very confusing look in the Courseware instead) Week 8 Lecure 3: Problems 49, 5 Fourier lysis Coursewre pp 6-7 (do look Frech very cofusig look i he Coursewre ised) Fourier lysis ivolves ddig wves d heir hrmoics, so i would hve urlly followed fer he

More information

Functions, Limit, And Continuity

Functions, Limit, And Continuity Fucios, Limi d coiuiy of fucio Fucios, Limi, Ad Coiuiy. Defiiio of fucio A fucio is rule of correspodece h ssocies wih ech ojec i oe se clled f from secod se. The se of ll vlues so oied is he domi, sigle

More information

Existence Of Solutions For Nonlinear Fractional Differential Equation With Integral Boundary Conditions

Existence Of Solutions For Nonlinear Fractional Differential Equation With Integral Boundary Conditions Reserch Ivey: Ieriol Jourl Of Egieerig Ad Sciece Vol., Issue (April 3), Pp 8- Iss(e): 78-47, Iss(p):39-6483, Www.Reserchivey.Com Exisece Of Soluios For Nolier Frciol Differeil Equio Wih Iegrl Boudry Codiios,

More information

Special Functions. Leon M. Hall. Professor of Mathematics University of Missouri-Rolla. Copyright c 1995 by Leon M. Hall. All rights reserved.

Special Functions. Leon M. Hall. Professor of Mathematics University of Missouri-Rolla. Copyright c 1995 by Leon M. Hall. All rights reserved. Specil Fucios Leo M. Hll Professor of Mhemics Uiversiy of Missouri-Roll Copyrigh c 995 y Leo M. Hll. All righs reserved. Chper 5. Orhogol Fucios 5.. Geerig Fucios Cosider fucio f of wo vriles, ( x,), d

More information

NOTES ON BERNOULLI NUMBERS AND EULER S SUMMATION FORMULA. B r = [m = 0] r

NOTES ON BERNOULLI NUMBERS AND EULER S SUMMATION FORMULA. B r = [m = 0] r NOTES ON BERNOULLI NUMBERS AND EULER S SUMMATION FORMULA MARK WILDON. Beroulli umbers.. Defiiio. We defie he Beroulli umbers B m for m by m ( m + ( B r [m ] r r Beroulli umbers re med fer Joh Beroulli

More information

HOMEWORK 6 - INTEGRATION. READING: Read the following parts from the Calculus Biographies that I have given (online supplement of our textbook):

HOMEWORK 6 - INTEGRATION. READING: Read the following parts from the Calculus Biographies that I have given (online supplement of our textbook): MAT 3 CALCULUS I 5.. Dokuz Eylül Uiversiy Fculy of Sciece Deprme of Mhemics Isrucors: Egi Mermu d Cell Cem Srıoğlu HOMEWORK 6 - INTEGRATION web: hp://kisi.deu.edu.r/egi.mermu/ Tebook: Uiversiy Clculus,

More information

F.Y. Diploma : Sem. II [CE/CR/CS] Applied Mathematics

F.Y. Diploma : Sem. II [CE/CR/CS] Applied Mathematics F.Y. Diplom : Sem. II [CE/CR/CS] Applied Mhemics Prelim Quesio Pper Soluio Q. Aemp y FIVE of he followig : [0] Q. () Defie Eve d odd fucios. [] As.: A fucio f() is sid o e eve fucio if f() f() A fucio

More information

Suggested Solution for Pure Mathematics 2011 By Y.K. Ng (last update: 8/4/2011) Paper I. (b) (c)

Suggested Solution for Pure Mathematics 2011 By Y.K. Ng (last update: 8/4/2011) Paper I. (b) (c) per I. Le α 7 d β 7. The α d β re he roos o he equio, such h α α, β β, --- α β d αβ. For, α β For, α β α β αβ 66 The seme is rue or,. ssume Cosider, α β d α β y deiiio α α α α β or some posiive ieer.

More information

Reinforcement Learning

Reinforcement Learning Reiforceme Corol lerig Corol polices h choose opiml cios Q lerig Covergece Chper 13 Reiforceme 1 Corol Cosider lerig o choose cios, e.g., Robo lerig o dock o bery chrger o choose cios o opimize fcory oupu

More information

SLOW INCREASING FUNCTIONS AND THEIR APPLICATIONS TO SOME PROBLEMS IN NUMBER THEORY

SLOW INCREASING FUNCTIONS AND THEIR APPLICATIONS TO SOME PROBLEMS IN NUMBER THEORY VOL. 8, NO. 7, JULY 03 ISSN 89-6608 ARPN Jourl of Egieerig d Applied Sciece 006-03 Ai Reerch Publihig Nework (ARPN). All righ reerved. www.rpjourl.com SLOW INCREASING FUNCTIONS AND THEIR APPLICATIONS TO

More information

ECE 636: Systems identification

ECE 636: Systems identification ECE 636: Sysems ideificio Lecures 7 8 Predicio error mehods Se spce models Coiuous ime lier se spce spce model: x ( = Ax( + Bu( + w( y( = Cx( + υ( A:, B: m, C: Discree ime lier se spce model: x( + = A(

More information

ONE RANDOM VARIABLE F ( ) [ ] x P X x x x 3

ONE RANDOM VARIABLE F ( ) [ ] x P X x x x 3 The Cumulive Disribuio Fucio (cd) ONE RANDOM VARIABLE cd is deied s he probbiliy o he eve { x}: F ( ) [ ] x P x x - Applies o discree s well s coiuous RV. Exmple: hree osses o coi x 8 3 x 8 8 F 3 3 7 x

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information

ERROR ESTIMATES FOR APPROXIMATING THE FOURIER TRANSFORM OF FUNCTIONS OF BOUNDED VARIATION

ERROR ESTIMATES FOR APPROXIMATING THE FOURIER TRANSFORM OF FUNCTIONS OF BOUNDED VARIATION ERROR ESTIMATES FOR APPROXIMATING THE FOURIER TRANSFORM OF FUNCTIONS OF BOUNDED VARIATION N.S. BARNETT, S.S. DRAGOMIR, AND G. HANNA Absrc. I his pper we poi ou pproximio for he Fourier rsform for fucios

More information

Taylor Polynomials. The Tangent Line. (a, f (a)) and has the same slope as the curve y = f (x) at that point. It is the best

Taylor Polynomials. The Tangent Line. (a, f (a)) and has the same slope as the curve y = f (x) at that point. It is the best Tylor Polyomils Let f () = e d let p() = 1 + + 1 + 1 6 3 Without usig clcultor, evlute f (1) d p(1) Ok, I m still witig With little effort it is possible to evlute p(1) = 1 + 1 + 1 (144) + 6 1 (178) =

More information

Solutions to selected problems from the midterm exam Math 222 Winter 2015

Solutions to selected problems from the midterm exam Math 222 Winter 2015 Soluios o seleced problems from he miderm eam Mah Wier 5. Derive he Maclauri series for he followig fucios. (cf. Pracice Problem 4 log( + (a L( d. Soluio: We have he Maclauri series log( + + 3 3 4 4 +...,

More information

Department of Mathematical and Statistical Sciences University of Alberta

Department of Mathematical and Statistical Sciences University of Alberta MATH 4 (R) Wier 008 Iermediae Calculus I Soluios o Problem Se # Due: Friday Jauary 8, 008 Deparme of Mahemaical ad Saisical Scieces Uiversiy of Albera Quesio. [Sec.., #] Fid a formula for he geeral erm

More information

ON SOME FRACTIONAL PARABOLIC EQUATIONS DRIVEN BY FRACTIONAL GAUSSIAN NOISE

ON SOME FRACTIONAL PARABOLIC EQUATIONS DRIVEN BY FRACTIONAL GAUSSIAN NOISE IJRRAS 6 3) Februry www.rppress.com/volumes/vol6issue3/ijrras_6_3_.pdf ON SOME FRACIONAL ARABOLIC EQUAIONS RIVEN BY FRACIONAL GAUSSIAN NOISE Mhmoud M. El-Bori & hiri El-Sid El-Ndi Fculy of Sciece Alexdri

More information

Local Fractional Kernel Transform in Fractal Space and Its Applications

Local Fractional Kernel Transform in Fractal Space and Its Applications From he SelecedWorks of Xio-J Yg 22 Locl Frciol Kerel Trsform i Frcl Spce d Is Applicios Yg Xioj Aville : hps://works.epress.com/yg_ioj/3/ Advces i Compuiol Mhemics d is Applicios 86 Vol. No. 2 22 Copyrigh

More information

S n. = n. Sum of first n terms of an A. P is

S n. = n. Sum of first n terms of an A. P is PROGREION I his secio we discuss hree impora series amely ) Arihmeic Progressio (A.P), ) Geomeric Progressio (G.P), ad 3) Harmoic Progressio (H.P) Which are very widely used i biological scieces ad humaiies.

More information

Extremal graph theory II: K t and K t,t

Extremal graph theory II: K t and K t,t Exremal graph heory II: K ad K, Lecure Graph Theory 06 EPFL Frak de Zeeuw I his lecure, we geeralize he wo mai heorems from he las lecure, from riagles K 3 o complee graphs K, ad from squares K, o complee

More information

PROGRESSIONS AND SERIES

PROGRESSIONS AND SERIES PROGRESSIONS AND SERIES A sequece is lso clled progressio. We ow study three importt types of sequeces: () The Arithmetic Progressio, () The Geometric Progressio, () The Hrmoic Progressio. Arithmetic Progressio.

More information

Calculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws.

Calculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws. Limi of a fucio.. Oe-Sided..... Ifiie limis Verical Asympoes... Calculaig Usig he Limi Laws.5 The Squeeze Theorem.6 The Precise Defiiio of a Limi......7 Coiuiy.8 Iermediae Value Theorem..9 Refereces..

More information

L-functions and Class Numbers

L-functions and Class Numbers L-fucios ad Class Numbers Sude Number Theory Semiar S. M.-C. 4 Sepember 05 We follow Romyar Sharifi s Noes o Iwasawa Theory, wih some help from Neukirch s Algebraic Number Theory. L-fucios of Dirichle

More information

Review Exercises for Chapter 9

Review Exercises for Chapter 9 0_090R.qd //0 : PM Page 88 88 CHAPTER 9 Ifiie Series I Eercises ad, wrie a epressio for he h erm of he sequece..,., 5, 0,,,, 0,... 7,... I Eercises, mach he sequece wih is graph. [The graphs are labeled

More information

Graphing Review Part 3: Polynomials

Graphing Review Part 3: Polynomials Grphig Review Prt : Polomils Prbols Recll, tht the grph of f ( ) is prbol. It is eve fuctio, hece it is smmetric bout the bout the -is. This mes tht f ( ) f ( ). Its grph is show below. The poit ( 0,0)

More information

Contraction Mapping Principle Approach to Differential Equations

Contraction Mapping Principle Approach to Differential Equations epl Journl of Science echnology 0 (009) 49-53 Conrcion pping Principle pproch o Differenil Equions Bishnu P. Dhungn Deprmen of hemics, hendr Rn Cmpus ribhuvn Universiy, Khmu epl bsrc Using n eension of

More information

Forced Oscillation of Nonlinear Impulsive Hyperbolic Partial Differential Equation with Several Delays

Forced Oscillation of Nonlinear Impulsive Hyperbolic Partial Differential Equation with Several Delays Jourl of Applied Mhemics d Physics, 5, 3, 49-55 Published Olie November 5 i SciRes hp://wwwscirporg/ourl/mp hp://dxdoiorg/436/mp5375 Forced Oscillio of Nolier Impulsive Hyperbolic Pril Differeil Equio

More information

Experiment 6: Fourier Series

Experiment 6: Fourier Series Fourier Series Experime 6: Fourier Series Theory A Fourier series is ifiie sum of hrmoic fucios (sies d cosies) wih every erm i he series hvig frequecy which is iegrl muliple of some pricipl frequecy d

More information

Math 2414 Homework Set 7 Solutions 10 Points

Math 2414 Homework Set 7 Solutions 10 Points Mah Homework Se 7 Soluios 0 Pois #. ( ps) Firs verify ha we ca use he iegral es. The erms are clearly posiive (he epoeial is always posiive ad + is posiive if >, which i is i his case). For decreasig we

More information

f(t)dt 2δ f(x) f(t)dt 0 and b f(t)dt = 0 gives F (b) = 0. Since F is increasing, this means that

f(t)dt 2δ f(x) f(t)dt 0 and b f(t)dt = 0 gives F (b) = 0. Since F is increasing, this means that Uiversity of Illiois t Ur-Chmpig Fll 6 Mth 444 Group E3 Itegrtio : correctio of the exercises.. ( Assume tht f : [, ] R is cotiuous fuctio such tht f(x for ll x (,, d f(tdt =. Show tht f(x = for ll x [,

More information

Comparison between Fourier and Corrected Fourier Series Methods

Comparison between Fourier and Corrected Fourier Series Methods Malaysia Joural of Mahemaical Scieces 7(): 73-8 (13) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES Joural homepage: hp://eispem.upm.edu.my/oural Compariso bewee Fourier ad Correced Fourier Series Mehods 1

More information

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k.

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k. . Computtio of Fourier Series I this sectio, we compute the Fourier coefficiets, f ( x) cos( x) b si( x) d b, i the Fourier series To do this, we eed the followig result o the orthogolity of the trigoometric

More information

The limit comparison test

The limit comparison test Roerto s Notes o Ifiite Series Chpter : Covergece tests Sectio 4 The limit compriso test Wht you eed to kow lredy: Bsics of series d direct compriso test. Wht you c ler here: Aother compriso test tht does

More information

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory

Ideal Amplifier/Attenuator. Memoryless. where k is some real constant. Integrator. System with memory Liear Time-Ivaria Sysems (LTI Sysems) Oulie Basic Sysem Properies Memoryless ad sysems wih memory (saic or dyamic) Causal ad o-causal sysems (Causaliy) Liear ad o-liear sysems (Lieariy) Sable ad o-sable

More information

Review for the Midterm Exam.

Review for the Midterm Exam. Review for he iderm Exm Rememer! Gross re e re Vriles suh s,, /, p / p, r, d R re gross res 2 You should kow he disiio ewee he fesile se d he udge se, d kow how o derive hem The Fesile Se Wihou goverme

More information

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x)

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x) Properies of Logrihms Solving Eponenil nd Logrihmic Equions Properies of Logrihms Produc Rule ( ) log mn = log m + log n ( ) log = log + log Properies of Logrihms Quoien Rule log m = logm logn n log7 =

More information

LIMITS OF FUNCTIONS (I)

LIMITS OF FUNCTIONS (I) LIMITS OF FUNCTIO (I ELEMENTARY FUNCTIO: (Elemeary fucios are NOT piecewise fucios Cosa Fucios: f(x k, where k R Polyomials: f(x a + a x + a x + a x + + a x, where a, a,..., a R Raioal Fucios: f(x P (x,

More information

Integration and Differentiation

Integration and Differentiation ome Clculus bckgroud ou should be fmilir wih, or review, for Mh 404 I will be, for he mos pr, ssumed ou hve our figerips he bsics of (mulivrible) fucios, clculus, d elemer differeil equios If here hs bee

More information

2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i)

2 f(x) dx = 1, 0. 2f(x 1) dx d) 1 4t t6 t. t 2 dt i) Mah PracTes Be sure o review Lab (ad all labs) There are los of good quesios o i a) Sae he Mea Value Theorem ad draw a graph ha illusraes b) Name a impora heorem where he Mea Value Theorem was used i he

More information

ON BILATERAL GENERATING FUNCTIONS INVOLVING MODIFIED JACOBI POLYNOMIALS

ON BILATERAL GENERATING FUNCTIONS INVOLVING MODIFIED JACOBI POLYNOMIALS Jourl of Sciece d Ars Yer 4 No 227-6 24 ORIINAL AER ON BILATERAL ENERATIN FUNCTIONS INVOLVIN MODIFIED JACOBI OLYNOMIALS CHANDRA SEKHAR BERA Muscri received: 424; Acceed er: 3524; ublished olie: 3624 Absrc

More information

Extension of Hardy Inequality on Weighted Sequence Spaces

Extension of Hardy Inequality on Weighted Sequence Spaces Jourl of Scieces Islic Reublic of Ir 20(2): 59-66 (2009) Uiversiy of ehr ISS 06-04 h://sciecesucir Eesio of Hrdy Iequliy o Weighed Sequece Sces R Lshriour d D Foroui 2 Dere of Mheics Fculy of Mheics Uiversiy

More information

An interesting result about subset sums. Nitu Kitchloo. Lior Pachter. November 27, Abstract

An interesting result about subset sums. Nitu Kitchloo. Lior Pachter. November 27, Abstract A ieresig resul abou subse sums Niu Kichloo Lior Pacher November 27, 1993 Absrac We cosider he problem of deermiig he umber of subses B f1; 2; : : :; g such ha P b2b b k mod, where k is a residue class

More information

Degree of Approximation of Conjugate of Signals (Functions) by Lower Triangular Matrix Operator

Degree of Approximation of Conjugate of Signals (Functions) by Lower Triangular Matrix Operator Alied Mhemics 2 2 448-452 doi:.4236/m.2.2226 Pulished Olie Decemer 2 (h://www.scirp.org/jourl/m) Degree of Aroimio of Cojuge of Sigls (Fucios) y Lower Trigulr Mri Oeror Asrc Vishu Nry Mishr Huzoor H. Kh

More information

Using Linnik's Identity to Approximate the Prime Counting Function with the Logarithmic Integral

Using Linnik's Identity to Approximate the Prime Counting Function with the Logarithmic Integral Usig Lii's Ideiy o Approimae he Prime Couig Fucio wih he Logarihmic Iegral Naha McKezie /26/2 aha@icecreambreafas.com Summary:This paper will show ha summig Lii's ideiy from 2 o ad arragig erms i a cerai

More information

On computing two special cases of Gauss hypergeometric function

On computing two special cases of Gauss hypergeometric function O comuig wo secil cses of Guss hyergeomeric fucio Mohmmd Msjed-Jmei Wolfrm Koef b * Derme of Mhemics K.N.Toosi Uiversiy of Techology P.O.Bo 65-68 Tehr Ir E-mil: mmjmei@u.c.ir mmjmei@yhoo.com b* Isiue of

More information

DIFFERENCE EQUATIONS

DIFFERENCE EQUATIONS DIFFERECE EQUATIOS Lier Cos-Coeffiie Differee Eqios Differee Eqios I disree-ime ssems, esseil feres of ip d op sigls pper ol speifi iss of ime, d he m o e defied ewee disree ime seps or he m e os. These

More information

N! AND THE GAMMA FUNCTION

N! AND THE GAMMA FUNCTION N! AND THE GAMMA FUNCTION Cosider he produc of he firs posiive iegers- 3 4 5 6 (-) =! Oe calls his produc he facorial ad has ha produc of he firs five iegers equals 5!=0. Direcly relaed o he discree! fucio

More information

On Absolute Indexed Riesz Summability of Orthogonal Series

On Absolute Indexed Riesz Summability of Orthogonal Series Ieriol Jourl of Couiol d Alied Mheics. ISSN 89-4966 Volue 3 Nuer (8). 55-6 eserch Idi Pulicios h:www.riulicio.co O Asolue Ideed iesz Suiliy of Orhogol Series L. D. Je S. K. Piry *. K. Ji 3 d. Sl 4 eserch

More information

UNIT 1: ANALYTICAL METHODS FOR ENGINEERS

UNIT 1: ANALYTICAL METHODS FOR ENGINEERS UNIT : ANALYTICAL METHODS FOR ENGINEERS Ui code: A// QCF Level: Credi vale: OUTCOME TUTORIAL SERIES Ui coe Be able o aalyse ad model egieerig siaios ad solve problems sig algebraic mehods Algebraic mehods:

More information

A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY

A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY U.P.B. Sci. Bull., Series A, Vol. 78, Iss. 2, 206 ISSN 223-7027 A TAUBERIAN THEOREM FOR THE WEIGHTED MEAN METHOD OF SUMMABILITY İbrahim Çaak I his paper we obai a Tauberia codiio i erms of he weighed classical

More information

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6.

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6. [~ o o :- o o ill] i 1. Mrices, Vecors, nd Guss-Jordn Eliminion 1 x y = = - z= The soluion is ofen represened s vecor: n his exmple, he process of eliminion works very smoohly. We cn elimine ll enries

More information

Online Supplement to Reactive Tabu Search in a Team-Learning Problem

Online Supplement to Reactive Tabu Search in a Team-Learning Problem Olie Suppleme o Reacive abu Search i a eam-learig Problem Yueli She School of Ieraioal Busiess Admiisraio, Shaghai Uiversiy of Fiace ad Ecoomics, Shaghai 00433, People s Republic of Chia, she.yueli@mail.shufe.edu.c

More information

Transient Solution of the M/M/C 1 Queue with Additional C 2 Servers for Longer Queues and Balking

Transient Solution of the M/M/C 1 Queue with Additional C 2 Servers for Longer Queues and Balking Jourl of Mhemics d Sisics 4 (): 2-25, 28 ISSN 549-3644 28 Sciece ublicios Trsie Soluio of he M/M/C Queue wih Addiiol C 2 Servers for Loger Queues d Blkig R. O. Al-Seedy, A. A. El-Sherbiy,,2 S. A. EL-Shehwy

More information

Supplement for SADAGRAD: Strongly Adaptive Stochastic Gradient Methods"

Supplement for SADAGRAD: Strongly Adaptive Stochastic Gradient Methods Suppleme for SADAGRAD: Srogly Adapive Sochasic Gradie Mehods" Zaiyi Che * 1 Yi Xu * Ehog Che 1 iabao Yag 1. Proof of Proposiio 1 Proposiio 1. Le ɛ > 0 be fixed, H 0 γi, γ g, EF (w 1 ) F (w ) ɛ 0 ad ieraio

More information

Limit of a function:

Limit of a function: - Limit of fuctio: We sy tht f ( ) eists d is equl with (rel) umer L if f( ) gets s close s we wt to L if is close eough to (This defiitio c e geerlized for L y syig tht f( ) ecomes s lrge (or s lrge egtive

More information

FIXED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE

FIXED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE Mohia & Samaa, Vol. 1, No. II, December, 016, pp 34-49. ORIGINAL RESEARCH ARTICLE OPEN ACCESS FIED FUZZY POINT THEOREMS IN FUZZY METRIC SPACE 1 Mohia S. *, Samaa T. K. 1 Deparme of Mahemaics, Sudhir Memorial

More information

The Trigonometric Representation of Complex Type Number System

The Trigonometric Representation of Complex Type Number System Ieriol Jourl of Scieific d Reserch Pulicios Volume 7 Issue Ocoer 7 587 ISSN 5-353 The Trigoomeric Represeio of Complex Type Numer Sysem ThymhyPio Jude Nvih Deprme of Mhemics Eser Uiversiy Sri Lk Asrc-

More information

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS) Mthemtics Revisio Guides Itegrtig Trig, Log d Ep Fuctios Pge of MK HOME TUITION Mthemtics Revisio Guides Level: AS / A Level AQA : C Edecel: C OCR: C OCR MEI: C INTEGRATION TECHNIQUES (TRIG, LOG, EXP FUNCTIONS)

More information

Approximate Integration

Approximate Integration Study Sheet (7.7) Approimte Itegrtio I this sectio, we will ler: How to fid pproimte vlues of defiite itegrls. There re two situtios i which it is impossile to fid the ect vlue of defiite itegrl. Situtio:

More information

Moment Generating Function

Moment Generating Function 1 Mome Geeraig Fucio m h mome m m m E[ ] x f ( x) dx m h ceral mome m m m E[( ) ] ( ) ( x ) f ( x) dx Mome Geeraig Fucio For a real, M () E[ e ] e k x k e p ( x ) discree x k e f ( x) dx coiuous Example

More information

1 Notes on Little s Law (l = λw)

1 Notes on Little s Law (l = λw) Copyrigh c 26 by Karl Sigma Noes o Lile s Law (l λw) We cosider here a famous ad very useful law i queueig heory called Lile s Law, also kow as l λw, which assers ha he ime average umber of cusomers i

More information

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function ENGR 1990 Engineering Mhemics The Inegrl of Funcion s Funcion Previously, we lerned how o esime he inegrl of funcion f( ) over some inervl y dding he res of finie se of rpezoids h represen he re under

More information

September 20 Homework Solutions

September 20 Homework Solutions College of Engineering nd Compuer Science Mechnicl Engineering Deprmen Mechnicl Engineering A Seminr in Engineering Anlysis Fll 7 Number 66 Insrucor: Lrry Creo Sepember Homework Soluions Find he specrum

More information

VARIATIONAL ITERATION METHOD (VIM) FOR SOLVING PARTIAL INTEGRO-DIFFERENTIAL EQUATIONS

VARIATIONAL ITERATION METHOD (VIM) FOR SOLVING PARTIAL INTEGRO-DIFFERENTIAL EQUATIONS Jourl of Theoreicl d Applied Iformio Techology h Jue 16. Vol.88. No. 5-16 JATIT & LLS. All righs reserved. ISSN: 199-8645 www.ji.org E-ISSN: 1817-195 VARIATIONAL ITERATION ETHOD VI FOR SOLVING PARTIAL

More information

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1.

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1. GRAPHING LINEAR EQUATIONS Qudrt II Qudrt I ORDERED PAIR: The first umer i the ordered pir is the -coordite d the secod umer i the ordered pir is the y-coordite. (, ) Origi ( 0, 0 ) _-is Lier Equtios Qudrt

More information

( a n ) converges or diverges.

( a n ) converges or diverges. Chpter Ifiite Series Pge of Sectio E Rtio Test Chpter : Ifiite Series By the ed of this sectio you will be ble to uderstd the proof of the rtio test test series for covergece by pplyig the rtio test pprecite

More information

Lecture 15 First Properties of the Brownian Motion

Lecture 15 First Properties of the Brownian Motion Lecure 15: Firs Properies 1 of 8 Course: Theory of Probabiliy II Term: Sprig 2015 Isrucor: Gorda Zikovic Lecure 15 Firs Properies of he Browia Moio This lecure deals wih some of he more immediae properies

More information

Math 6710, Fall 2016 Final Exam Solutions

Math 6710, Fall 2016 Final Exam Solutions Mah 67, Fall 6 Fial Exam Soluios. Firs, a sude poied ou a suble hig: if P (X i p >, he X + + X (X + + X / ( evaluaes o / wih probabiliy p >. This is roublesome because a radom variable is supposed o be

More information

Infinite Series Sequences: terms nth term Listing Terms of a Sequence 2 n recursively defined n+1 Pattern Recognition for Sequences Ex:

Infinite Series Sequences: terms nth term Listing Terms of a Sequence 2 n recursively defined n+1 Pattern Recognition for Sequences Ex: Ifiite Series Sequeces: A sequece i defied s fuctio whose domi is the set of positive itegers. Usully it s esier to deote sequece i subscript form rther th fuctio ottio.,, 3, re the terms of the sequece

More information

A new approach to Kudryashov s method for solving some nonlinear physical models

A new approach to Kudryashov s method for solving some nonlinear physical models Ieriol Jourl of Physicl Scieces Vol. 7() pp. 860-866 0 My 0 Avilble olie hp://www.cdeicourls.org/ijps DOI: 0.897/IJPS.07 ISS 99-90 0 Acdeic Jourls Full Legh Reserch Pper A ew pproch o Kudryshov s ehod

More information

The analysis of the method on the one variable function s limit Ke Wu

The analysis of the method on the one variable function s limit Ke Wu Ieraioal Coferece o Advaces i Mechaical Egieerig ad Idusrial Iformaics (AMEII 5) The aalysis of he mehod o he oe variable fucio s i Ke Wu Deparme of Mahemaics ad Saisics Zaozhuag Uiversiy Zaozhuag 776

More information

Chapter 5: The pn Junction

Chapter 5: The pn Junction Cher 5: The ucio Noequilibrium ecess crriers i semicoducors Crrier geerio d recombiio Mhemicl lysis of ecess crriers Ambiolr rsor The jucio Bsic srucure of he jucio Zero lied bis Reverse lied bis No-uiformly

More information

SUTCLIFFE S NOTES: CALCULUS 2 SWOKOWSKI S CHAPTER 11

SUTCLIFFE S NOTES: CALCULUS 2 SWOKOWSKI S CHAPTER 11 UTCLIFFE NOTE: CALCULU WOKOWKI CHAPTER Ifiite eries Coverget or Diverget eries Cosider the sequece If we form the ifiite sum 0, 00, 000, 0 00 000, we hve wht is clled ifiite series We wt to fid the sum

More information

SUTCLIFFE S NOTES: CALCULUS 2 SWOKOWSKI S CHAPTER 11

SUTCLIFFE S NOTES: CALCULUS 2 SWOKOWSKI S CHAPTER 11 SUTCLIFFE S NOTES: CALCULUS SWOKOWSKI S CHAPTER Ifiite Series.5 Altertig Series d Absolute Covergece Next, let us cosider series with both positive d egtive terms. The simplest d most useful is ltertig

More information

{ } { S n } is monotonically decreasing if Sn

{ } { S n } is monotonically decreasing if Sn Sequece A sequece is fuctio whose domi of defiitio is the set of turl umers. Or it c lso e defied s ordered set. Nottio: A ifiite sequece is deoted s { } S or { S : N } or { S, S, S,...} or simply s {

More information

Solution of Laplace s Differential Equation and Fractional Differential Equation of That Type

Solution of Laplace s Differential Equation and Fractional Differential Equation of That Type Applie Mheics 3 4 6-36 Pulishe Olie oveer 3 (hp://wwwscirporg/jourl/) hp://oiorg/436/34a5 Soluio of Lplce s iffereil Equio Frciol iffereil Equio of Th Type Tohru Mori Ke-ichi So Tohou Uiversiy Sei Jp College

More information

10.5 Power Series. In this section, we are going to start talking about power series. A power series is a series of the form

10.5 Power Series. In this section, we are going to start talking about power series. A power series is a series of the form 0.5 Power Series I the lst three sectios, we ve spet most of tht time tlkig bout how to determie if series is coverget or ot. Now it is time to strt lookig t some specific kids of series d we will evetully

More information

Sampling Example. ( ) δ ( f 1) (1/2)cos(12πt), T 0 = 1

Sampling Example. ( ) δ ( f 1) (1/2)cos(12πt), T 0 = 1 Samplig Example Le x = cos( 4π)cos( π). The fudameal frequecy of cos 4π fudameal frequecy of cos π is Hz. The ( f ) = ( / ) δ ( f 7) + δ ( f + 7) / δ ( f ) + δ ( f + ). ( f ) = ( / 4) δ ( f 8) + δ ( f

More information

1. Solve by the method of undetermined coefficients and by the method of variation of parameters. (4)

1. Solve by the method of undetermined coefficients and by the method of variation of parameters. (4) 7 Differeial equaios Review Solve by he mehod of udeermied coefficies ad by he mehod of variaio of parameers (4) y y = si Soluio; we firs solve he homogeeous equaio (4) y y = 4 The correspodig characerisic

More information

 n. A Very Interesting Example + + = d. + x3. + 5x4. math 131 power series, part ii 7. One of the first power series we examined was. 2!

 n. A Very Interesting Example + + = d. + x3. + 5x4. math 131 power series, part ii 7. One of the first power series we examined was. 2! mth power series, prt ii 7 A Very Iterestig Emple Oe of the first power series we emied ws! + +! + + +!! + I Emple 58 we used the rtio test to show tht the itervl of covergece ws (, ) Sice the series coverges

More information

STK4080/9080 Survival and event history analysis

STK4080/9080 Survival and event history analysis STK48/98 Survival ad eve hisory aalysis Marigales i discree ime Cosider a sochasic process The process M is a marigale if Lecure 3: Marigales ad oher sochasic processes i discree ime (recap) where (formally

More information

SUMMATION OF INFINITE SERIES REVISITED

SUMMATION OF INFINITE SERIES REVISITED SUMMATION OF INFINITE SERIES REVISITED I several aricles over he las decade o his web page we have show how o sum cerai iiie series icludig he geomeric series. We wa here o eed his discussio o he geeral

More information

BINOMIAL THEOREM OBJECTIVE PROBLEMS in the expansion of ( 3 +kx ) are equal. Then k =

BINOMIAL THEOREM OBJECTIVE PROBLEMS in the expansion of ( 3 +kx ) are equal. Then k = wwwskshieduciocom BINOMIAL HEOREM OBJEIVE PROBLEMS he coefficies of, i e esio of k e equl he k /7 If e coefficie of, d ems i e i AP, e e vlue of is he coefficies i e,, 7 ems i e esio of e i AP he 7 7 em

More information

Integral Equations and their Relationship to Differential Equations with Initial Conditions

Integral Equations and their Relationship to Differential Equations with Initial Conditions Scece Refleco SR Vol 6 wwwscecereflecocom Geerl Leers Mhemcs GLM 6 3-3 Geerl Leers Mhemcs GLM Wese: hp://wwwscecereflecocom/geerl-leers--mhemcs/ Geerl Leers Mhemcs Scece Refleco Iegrl Equos d her Reloshp

More information

λiv Av = 0 or ( λi Av ) = 0. In order for a vector v to be an eigenvector, it must be in the kernel of λi

λiv Av = 0 or ( λi Av ) = 0. In order for a vector v to be an eigenvector, it must be in the kernel of λi Liear lgebra Lecure #9 Noes This week s lecure focuses o wha migh be called he srucural aalysis of liear rasformaios Wha are he irisic properies of a liear rasformaio? re here ay fixed direcios? The discussio

More information

Chapter 7 Infinite Series

Chapter 7 Infinite Series MA Ifiite Series Asst.Prof.Dr.Supree Liswdi Chpter 7 Ifiite Series Sectio 7. Sequece A sequece c be thought of s list of umbers writte i defiite order:,,...,,... 2 The umber is clled the first term, 2

More information

Unit 1. Extending the Number System. 2 Jordan School District

Unit 1. Extending the Number System. 2 Jordan School District Uit Etedig the Number System Jord School District Uit Cluster (N.RN. & N.RN.): Etedig Properties of Epoets Cluster : Etedig properties of epoets.. Defie rtiol epoets d eted the properties of iteger epoets

More information

Pre-Calculus - Chapter 3 Sections Notes

Pre-Calculus - Chapter 3 Sections Notes Pre-Clculus - Chpter 3 Sectios 3.1-3.4- Notes Properties o Epoets (Review) 1. ( )( ) = + 2. ( ) =, (c) = 3. 0 = 1 4. - = 1/( ) 5. 6. c Epoetil Fuctios (Sectio 3.1) Deiitio o Epoetil Fuctios The uctio deied

More information

MTH 146 Class 11 Notes

MTH 146 Class 11 Notes 8.- Are of Surfce of Revoluion MTH 6 Clss Noes Suppose we wish o revolve curve C round n is nd find he surfce re of he resuling solid. Suppose f( ) is nonnegive funcion wih coninuous firs derivive on he

More information

Boundary Value Problems of Conformable. Fractional Differential Equation with Impulses

Boundary Value Problems of Conformable. Fractional Differential Equation with Impulses Applied Meicl Scieces Vol 2 28 o 8 377-397 HIKARI Ld www-irico ps://doiorg/2988/s28823 Boudry Vlue Probles of Coforble Frciol Differeil Equio wi Ipulses Arisr Tgvree Ci Tipryoo d Apisi Ppogpu Depre of

More information

Elementary Linear Algebra

Elementary Linear Algebra Elemetry Lier Alger Ato & Rorres, th Editio Lecture Set Chpter : Systems of Lier Equtios & Mtrices Chpter Cotets Itroductio to System of Lier Equtios Gussi Elimitio Mtrices d Mtri Opertios Iverses; Rules

More information

M3P14 EXAMPLE SHEET 1 SOLUTIONS

M3P14 EXAMPLE SHEET 1 SOLUTIONS M3P14 EXAMPLE SHEET 1 SOLUTIONS 1. Show tht for, b, d itegers, we hve (d, db) = d(, b). Sice (, b) divides both d b, d(, b) divides both d d db, d hece divides (d, db). O the other hd, there exist m d

More information

th m m m m central moment : E[( X X) ] ( X X) ( x X) f ( x)

th m m m m central moment : E[( X X) ] ( X X) ( x X) f ( x) 1 Trasform Techiques h m m m m mome : E[ ] x f ( x) dx h m m m m ceral mome : E[( ) ] ( ) ( x) f ( x) dx A coveie wa of fidig he momes of a radom variable is he mome geeraig fucio (MGF). Oher rasform echiques

More information

ALGEBRA. Set of Equations. have no solution 1 b1. Dependent system has infinitely many solutions

ALGEBRA. Set of Equations. have no solution 1 b1. Dependent system has infinitely many solutions Qudrtic Equtios ALGEBRA Remider theorem: If f() is divided b( ), the remider is f(). Fctor theorem: If ( ) is fctor of f(), the f() = 0. Ivolutio d Evlutio ( + b) = + b + b ( b) = + b b ( + b) 3 = 3 +

More information

Calculus BC 2015 Scoring Guidelines

Calculus BC 2015 Scoring Guidelines AP Calculus BC 5 Scorig Guidelies 5 The College Board. College Board, Advaced Placeme Program, AP, AP Ceral, ad he acor logo are regisered rademarks of he College Board. AP Ceral is he official olie home

More information

Solutions to Problems 3, Level 4

Solutions to Problems 3, Level 4 Soluios o Problems 3, Level 4 23 Improve he resul of Quesio 3 whe l. i Use log log o prove ha for real >, log ( {}log + 2 d log+ P ( + P ( d 2. Here P ( is defied i Quesio, ad parial iegraio has bee used.

More information

(A) 1 (B) 1 + (sin 1) (C) 1 (sin 1) (D) (sin 1) 1 (C) and g be the inverse of f. Then the value of g'(0) is. (C) a. dx (a > 0) is

(A) 1 (B) 1 + (sin 1) (C) 1 (sin 1) (D) (sin 1) 1 (C) and g be the inverse of f. Then the value of g'(0) is. (C) a. dx (a > 0) is [STRAIGHT OBJECTIVE TYPE] l Q. Th vlu of h dfii igrl, cos d is + (si ) (si ) (si ) Q. Th vlu of h dfii igrl si d whr [, ] cos cos Q. Vlu of h dfii igrl ( si Q. L f () = d ( ) cos 7 ( ) )d d g b h ivrs

More information