Stochastic modeling of nonlinear oscillators under combined Gaussian and Poisson White noise

Size: px
Start display at page:

Download "Stochastic modeling of nonlinear oscillators under combined Gaussian and Poisson White noise"

Transcription

1 Nonlinear Dynaics anuscrip No. will be insered by he edior Sochasic odeling of nonlinear oscillaors under cobined Gaussian Poisson Whie noise A viewpoin based on he energy conservaion law Xu Sun Jinqiao Duan Xiaofan Li Received: dae / Acceped: dae Absrac A sochasic differenial equaion odel is considered for nonlinear oscillaors under exciaions of cobined Gaussian Poisson whie noise. Since he soluions of sochasic differenial equaions can be inerpreed in ers of several ypes of sochasic inegrals, i is soeies confusing abou which inegral is acually appropriae. In order for he energy conservaion law o hold under cobined Gaussian Poisson whie noise exciaions, an appropriae sochasic inegral is inroduced in his paper. This sochasic inegral reduces o he Di Paola-Falsone inegral when he uliplicaive noise inensiy is infiniely differeniable wih respec o he sae. The sochasic inegral inroduced in his paper is applicable in ore general siuaions. Nuerical exaples are presened o illusrae he heoreical conclusion. Keywor nonlinear oscillaor non-gaussian whie noise Poisson whie noise sochasic differenial equaions sochasic inegrals X. Sun Deparen of Applied Maheaics Huazhong Universiy of Science Technology Wuhan 4374, Hubei, China Tel.: E-ail: xsun5@gail.co; xsun@hus.edu.cn J. Duan Deparen of Applied Maheaics Illinois Insiue of Technology, Chicago, IL 666, USA X. Li Deparen of Applied Maheaics Illinois Insiue of Technology, Chicago, IL 666, USA Sybols Descripion ie ass k siffness coefficien x displaceen depending on ie ẋ firs derivaive of x wih respec o ie. ẋ second derivaive of x wih respec o ie gx, ẋ a funcion of x ẋ which appears as a generalized force er fx, ẋ a funcion of x ẋ which appears as he coefficien of noise er B Brownian oion Ḃ Gaussian whie noise defined as he generalized ie derivaive of he Brownian oion B C Copound Poisson process Ċ Copound Poisson whie noise defined as he generalized ie derivaive of he copound Poisson process C N Poisson process λ inensiy paraeer of he Poisson process N b a consan represening he weigh of B in L c a consan represening he weigh of C in L U i a uni sep funcion a ie i δ i Dela funcion a ie i R i Ro variable represening he i-h ipulse in C L a sochasic process defined as bbcc L cobined Gaussian Poisson whie noise defined as he generalized ie derivaive of he sochasic process L x y sae variable defined as ẋ A A arix defined as k k ω a variable defined as Io calculus Sraonovich calculus Cs he lef lii of Cs a s Cs he jup size of Cs a s, defined as Cs Cs ẋ i, r he value of ẋs a s i as Cs juped fro C i o r

2 Xu Sun e al. Inroducion Differenial equaions are exensively used in odeling dynaical syses in science engineering. When dynaical syses are under ro influences, sochasic differenial equaions SDEs are ofen appropriae odels. The soluions of SDEs are inerpreed in ers of sochasic inegrals 5. Dynaical syses subjec o Gaussian whie noise are ofen odeled by SDEs wih Brownian oion, he soluions are popularly inerpreed by he Io inegral,. Alhough he Io inegral is self-consisen aheaically, i is no he only ype of sochasic inegrals for inerpreing SDEs. Oher sochasic inegrals, such as he Sraonovich inegral,, have also been used o inerpre an SDE as a sochasic inegral equaion. There is no righ or wrong choice when choosing eiher Io or Sraonovich inegrals aheaically, since he wo inegrals can be convered ino each oher, provided ha he inegr saisfies cerain soohness condiions,. However, hese sochasic inegrals have differen definiions, one ay be ore direcly relaed o a pracical siuaion han he oher. While he Io inegral is a reasonable choice in any applicaions including finance biology, he Sraonovich inegral is observed o be ore appropriae in physical engineering applicaions. The S- raonovich inegral has an exra er coparing wih he corresponding Io inegral: he so-called correcion er 6. Soe auhors 7, 8 aribue his correcion er o he conversion fro physical whie noise o ideal whie noise. Beyond he Io inegral Sraonovich inegral, i is recenly found ha he A-inegral he general α-inegral 9, are ore relevan o realiy in soe applicaions. Dynaical syses driven by non-gaussian whie noise, especially Poisson whie noise, have araced a lo of aenion recenly. Correcion ers for convering Io SDEs o Sraonovich SDEs wih Poisson whie noise are presened in, 3. The DiPaola-Falsone inegral has been deonsraed discussed by any auhors 4 also soe confusions 3, 4. In our recen work5, i is shown ha DiPaola-Falsone inegral is aheaically equivalen o he soluion of an ODE syse. Theoreically, any differen kin of sochasic inegrals ay be defined for Poisson whie noise, as in he siuaion for Gaussian whie noise. I is desirable o know which sochasic inegral is ore relevan o realiy. In his paper, we consider ro vibraion under exciaions of a class of non-gaussian whie noise in ers of sochasic processes wih jups, including Poisson whie noise, we will define a sochasic inegral such ha soe fundaenal physical law e.g., energy conservaion law is saisfied. To his end, we consider a vibraion syse as a ass-spring oscillaor wih ro exciaion.ẋ kx gx, ẋ fx, ẋ L, where represens he ass, k is he siffness coefficien of he spring, x is he displaceen depending on ie. Moreover, gx, ẋ fx, ẋ L represen he generalized force ers, which ay originae fro exernal or paraeric exciaions. Finally, L is a whie noise defined as he generalized iederivaive of a sochasic process L bb cc, where b c are consans, B is a Gaussian process, C is a copound Poisson process as follows C N i R i U i. 3 In Eq. 3, N represens he nuber of jups up o ie is a Poisson process wih inensiy paraeer λ, U i is a uni sep funcion a Heaviside funcion a i, R i is a ro variable represening he i-h ipulse. I follows fro ha L bḃ cċ, 4 where Ḃ is he Gaussian whie noise, Ċ is he Poisson whie noise expressed as Ċ N i R i δ i. 5 Noe ha 4 is a general noise odel including he Gaussian whie noise b, c, he Poisson whie noise b, c, he cobined Gaussian Poisson whie noise b c. The second-order equaion can be rewrien as a syse of firs order SDEs x x d ẋ k d ẋ d dl. gx, ẋ fx, ẋ 6 Since L is non-differeniable alos everywhere, 6 canno be inerpreed in he fraework of classical calculus. In fac he soluion of 6 is inerpreed wih a

3 Sochasic odeling of nonlinear oscillaors under cobined Gaussian Poisson Whie noise 3 sochasic inegral, x x xs ẋ ẋ k ẋs gxs, ẋs dls. 7 fxs, ẋs Defining y x, A ẋ k using he variaion of paraeers forula, he soluion o Eq., or Eq. 6, can also be rewrien as, y e A y e A s gxs, ẋs e A s dls, 8 fxs, ẋs x x where y is he iniial condiion. ẋ ẋ I can be verified ha e A I A! A cosω sinω ω,! ω sinω cosω 9 k where ω. Subsiuing 9 ino 8, we ge x cosωx sinω ẋ ω sin ω s gxs, ẋs ω sin ω s fxs, ẋs dls, ω ẋ ω sinωx cosωẋ cos ω s gxs, ẋs cos ω s fxs, ẋs dls. Noe ha he sochasic inegrals in Eqs. 7 or are ye o be defined. As saed earlier, he sochasic inegrals which can be used o inerpreed SDEs ay no be unique. In order o consruc a SDE odel ha is physically relevan o he real syse, we will propose a sochasic inegral such ha he fundaenal physical law e.g., energy conservaion law is saisfied. The inegral defined in his way urns ou o be ore general han he DiPaola-Falsone inegral, in fac, he laer is a special case when he noise inensiy f is infiniely differeniable wih respec o he sae. This paper is organized as follows. In Sec., we derive a sochasic inegral, saring fro he energy conservaion law, ha is suiable for he SDE odel of he nonlinear ro oscillaor 6. The relaion beween he proposed sochasic inegral he DiPaola- Falsone sochasic inegral is discussed in Sec. 3. Nuerical eho wih an illusraive exaple are presened in Sec. 4. Sochasic inegrals for nonlinear ro vibraion Now we define or derive a sochasic inegral so ha fundaenal physical laws, such as he energy conservaion or energy-work conservaion law, hold. As for he nonlinear oscillaor described by he SDE, we expec he energy-work conservaion be saisfied ẋ kx ẋ kx gxs, ẋs fxs, ẋs Ls dxs, where ẋ kx represens he oal echanical energy of he syse a ie, he inegr in he righ h side is he forcing er of. Equaion expresses ha he change in he oal echanical energy is equal o he work done by he exernal forces. Wriing in he for of sochasic inegral, we have ẋ kx gxs, ẋsẋs gxs, ẋsẋs ẋ kx fxs, ẋs Lsẋs fxs, ẋsẋs dls. As saed before, he sochasic inegral wih respec o L should be defined such ha he soluion of saisfies he energy conservaion law. I follows fro ha a sochasic inegral wih respec o L can be decoposed ino wo ers: sochasic inegral wih respec o B sochasic inegral wih respec o C. We define he wo ers separaely in he following subsecions.. Poisson whie noise When b c, he sochasic process as expressed in reduces o a copound Poisson process.

4 4 Xu Sun e al. Noe ha he jup size of Cs a ie s can be expressed as Cs Cs Cs, where Cs is he lef lii of Cs a s. Suppose Cs jups a ies i i,,, hen he soluion 7 can be wrien as x x ẋ ẋ k N i i ẋs, i xs fxs, ẋs dcs, gxs, ẋs 3 where N, as shown in 3, represens he nuber of jups upo ie. In he following, we shall derive he sochasic inegral wih respec o jups such ha he energy conservaion law is saisfied. Firs, le us exaine he changes in he syse a i-h jup occurred a ie i i N. Fro 3, he displaceen x is coninuous while he velociy ẋ undergoes an jup given by x i x i, ẋ i ẋ i i 4 fxs, ẋs dcs. i The change in he oal energy due o he i-h jup is ha in he kineic energy given by ẋ i ẋ i i i fxs, ẋsẋs dcs, 5 due o he coninuiy of he displaceen x across an jup. If he inegrals wih respec o jups are defined in he sense of Io, hen 4 5 becoe ẋ i ẋ i fx i, ẋ i C i, 6 ẋ i ẋ i fx i, ẋ i ẋ i C i, 7 respecively. Since C i, i is clear ha 6 conradic wih 7. This indicaes ha he energy conservaion law canno be saisfied when he inegrals wih respec o jups are inerpreed in he sense of Io. In he following, we shall show ha he inegrals should be inerpreed as a kind of Rieann inegral on he iaginary pah along he jup o saisfy he energy conservaion law. Le ẋ i, r be he value of ẋs a ie i as Cs juped fro C i o r. Then ẋ i, C i ẋ i ẋ i, C i ẋ i. Wih he inegrals being inerpreed as he Rieann inegral on he iaginary pah along he jup, he energy-work law 5 can be wrien as ẋ i, C i ẋ i, C i Ci C i fx i, ẋ i, rẋ i, r dr. 8 he soluion 4 becoes ẋ i, C i ẋ i, C i Ci C i fx i, ẋ i, r dr. 9 Since he jup size can be any value, i follows fro 8 9ha for any λ R, i is rue ha ẋ i, λ ẋ i, C i λ C i fx i, ẋ i, rẋ i, r dr, ẋ i, λ ẋ i, C i λ C i fx i, ẋ i, r dr. Taking derivaives of boh sides of wih respec o λ, respecively, we ge he idenical ordinary differenial equaion ODE d i, λ fx i, ẋ i, λ. Using he fac ha ẋ i, C i ẋ i ẋ i, C i ẋ i, i follows fro ha ẋ i ẋ i Y i C i, 3 where Y i C i is deerined by he iniial or erinal value proble of he ODE d dλ Y iλ fx i, Y iλ ẋ i, 4 Y i. Noe ha in 4, λ C i for C i > or C i λ for C i <. Coparing he original soluion expression 4 wih he new forula 3, i can be seen ha he las er in 4 should be defined as Y i C i, hence, he sochasic inegral fxs, ẋs dcs should be defined as fxs, ẋs dcs N i Y i C i, 5 where Y i C i is he soluion o he ODE 4, N represens he nuber of jups up o ie.

5 Sochasic odeling of nonlinear oscillaors under cobined Gaussian Poisson Whie noise 5. Gaussian whie noise I has been observed ha Sraonovich inegral, insead of Io inegral, is ore appropriae in soe physical syses under Gaussian whie noise. In his subsecion, we verify his known observaion in he conex of he above nonlinear ro oscillaor odel wih Gaussian whie noise, by deonsraing ha in order for he energy conservaion law o hold, he sochasic inegral us be Sraonovich. Noe ha his conclusion for Gaussian whie noise is no new, bu he derivaion is presened here o derive he observaion fro a differen perspecive i.e., energy conservaion law. Wih b c, i follows fro ha he sochasic process L reduces o a Brownian oion, becoe x cosωx sinω ẋ ω sin ω s gxs, ẋs ω sin ω s fxs, ẋs dbs, ω ẋ ω sinωx cosωẋ cos ω s gxs, ẋs cos ω s fxs, ẋs dbs. ẋ kx respecively. gxs, ẋsẋs ẋ kx 6 fxs, ẋsẋs dbs, 7 There are wo ypes of sochasic inegral exensively used for SDEs driven by Brownian oions: Io inegral Sraonovich inegral. Noe ha differen lieraure ay use differen noaion o denoe Io Sraonovich calculus. Throughou his paper, we use o denoe Io calculus, for Sraonovich calculus. In he sense of Io, 6 7 can be wrien as x cosωx sinω ẋ ω sin ω s gxs, ẋs ω sin ω s fxs, ẋs dbs, ω ẋ ω sinωx cosωẋ cos ω s gxs, ẋs cos ω s fxs, ẋs dbs. ẋ kx gxs, ẋsẋs ẋ kx 8 fxs, ẋsẋs dbs, 9 respecively. In he sense of Sraonovich, 6 7 can be wrien as x cosωx sinω ẋ ω sin ω s gxs, ẋs ω sin ω s fxs, ẋs dbs, ω ẋ ω sinωx cosωẋ cos ω s gxs, ẋs ẋ kx cos ω s fxs, ẋs dbs. gxs, ẋsẋs ẋ kx 3 fxs, ẋsẋs dbs, 3 respecively. Provided ha he funcion f is sufficien s- ooh, he soluions in Sraonovich inegrals, 3 3, can be convered ino he following fors wih Io

6 6 Xu Sun e al. inegrals x cosωx sinω ẋ ω sin ω s gxs, ẋs ω fxs, ẋsf ẋxs, ẋs sin ω s fxs, ẋs dbs, ω ẋ ω sinωx cosωẋ cos ω s gxs, ẋs ẋ kx fxs, ẋsf ẋxs, ẋs cos ω s fxs, ẋs dbs, ẋ kx gxs, ẋs f xs, ẋs fxs, ẋsf ẋxs, ẋsẋs 3 fxs, ẋsẋs dbs. 33 As shown in he Appendix, he soluion 3 saisfies he energy-work relaion 33, suggesing ha when he roness is odeled in sense of Sraonovich, he energy-work conservaion law is saisfied. On he oher h, in a siilar procedure as in he Appendix, i can be shown ha he energy-work law 9 conradics wih he soluion 8. Therefore, Sraonovich inegral insead of Io inegral should be used so ha his nonlinear ro oscillaor odel saisfies he energy conservaion law..3 Cobined Gaussian Poisson whie noise When boh b c, he exciaion is a cobined Gaussian Poisson whie noise. Cobining he resuls in he subsecions.., we find ha, in order o saisfy he energy-work conservion law, one has o inerpre he sochasic inegrals wih respec o Brownian oions as Sraonovich inegrals, he inegrals wih respec o jups as he su of soluions of soe firs order ODEs. Therefore, he soluion o is given by he expression 7, where he sochasic inegral is defined as fxs, ẋs dls b N fxs, ẋs dbs Y i L i, 34 i where L i cc i C i c C i. Recall ha, in 34, denoe inegrals in he Sraonovich sense, N represens he nuber of jups up o ie, Y i L i is he soluion o he ODE 4, where λ akes value of λ L i for L i > or L i λ for L i <. To suarize, he ain resul of his secion is o deonsrae ha in order o saisfy he energy conservaion law, he sochasic inegral wih respec o Poisson whie noise should be inerpreed as in equaion 5, he sochasic inegral wih respec o he cobined Gaussian Poisson whie noise should be inerpreed as in equaion 34. Relaionship beween he above sochasic inegrals soe oher sochasic inegrals will be revealed in he nex secion. 3 Relaion wih he Di Paola-Falsone sochasic inegral In his secion, we shall show ha he correcion er Y i L i, as given by he soluion o he ODE 4, is consisen wih he one proposed in he work by Di Paola Falsone,3, when he noise inensiy f is infiniely differeniable wih respec o he sae variable x. In oher wor, when he uliplicaive noise inensiy is infiniely sooh, he sochasic inegral inroduced in his paper reduces o he Di Paola-Falsone sochasic inegral. This eans ha he Di Paola-Falsone inegral is a special case of he s- ochasic inegral ha guaranees he energy conservaion law. The sochasic inegral inroduced in his paper is hus applicable in ore general siuaions. If f is infiniely differeniable wih respec o x so ha he he unique soluion of 4 is analyic e.g., expressible as a convergen Taylor series, hen we have he following convergen Taylor expansion for Y i L i Y i L i Y i d dλ Y iλ λ L i d! dλ Y iλ λ L i. 35

7 Sochasic odeling of nonlinear oscillaors under cobined Gaussian Poisson Whie noise 7 I follows fro 4 ha for any n, d n dλ n Y iλ d dy i λ { } d n dλ n Y iλ f x i, Y iλ ẋ i. 36 Subsiuing 36 ino 35, using he fac ha Y i, we ge Y i L i j f j x i, ẋ i j! L i j, 37 where f x, ẋ i fx i, ẋ i f j x, ẋ i f i x i, ẋ i λ fx i, ẋ i λ λ for j. 38 Thus he correcion er given by 37 is exacly he sae as he one proposed in,3. We have shown ha he correcion er Y i L i can be obained in wo ways: Eiher solving he iniial value proble o he ODE 4 or copuing he expansion 37. Noe ha he forer approach of solving 4 is applicable under uch ore general condiion han he laer one of evaluaing he infinie series 37, because he exisence of he soluion o he ODE only require fx, y o be Lipschiz coninuous, bu 37 des fx, y o be infiniely differeniable. Readers are referred o lieraure 5 for a deailed coparison of hese wo fors of expressions. The sochasic inegral, as defined in 34 4, is derived direcly fro he energy conservaion law. Alhough his inegral for is he essenially he sae as ha in our previous work 5, he derivaion here in he curren paper does no rely on DiPao-Flasones forula while 5 focuses on he rigorous proof of he relaionship beween he proposed sochasic inegral he DiPaola-Falsone forula. This inegral is applicable beyond he field of ro vibraion, as shown in 5. 4 Nuerical experiens Soluions of he SDE for a nonlinear oscillaor, defined by 7 34, can hardly be obained wih analyical eho. In his secion, he SDE is nuerically solved o verify he conclusion obained in secion. Consider he case wih boh Gaussian Poisson whie noises, dl b db c dc, wih he copound Poisson process given by 5. The nuerical procedure of he SDE for a nonlinear oscillaor defined by 7 34 is as follows. On each ie subinerval i < < i, i.e. when no jups occur, becoes dx ẋ d dẋ k x d gx, ẋ d b fx, ẋ dbs. 39 The above equaion can be convered ino Io SDE hen copued by convenional algorihs for Io S- DEs, such as Euler ehod, Milsein ehod, or oher high-order algorihs 6. A he ie i when an jup occurs, i follows fro 7 34 ha { x i x i, ẋ i ẋ i Y 4 i L i, where Y i L i is obained by solving he deerinisic ODE 4 using Runge-Kua or ulisep eho. Consider he following sochasic Duffing-van der Pol equaion.. x x ẋ x x 3 ẋ L, 4 wih he iniial condiion x ẋ. The SDE 4 can be wrien in for of wih, k, gx, ẋ x ẋ x 3 fx, ẋ ẋ. In he siulaion, we ake L as in wih b c, i.e. L B C, where C is a pure jup process given by 3 wih N being a Poisson process wih inensiy paraeer as λ 3.4 R i i,, N being ro nubers of he sard noral disribuion. Figure shows a saple pah of he driven process L. Case In his case, 4 or is inerpreed by In he siulaion, o inegrae 7 34 nuerically, we use Euler ehod o advance 39 when no jups occur, while evaluae 4 by solving 4 wih Euler ehod when jups arrive. Noe ha o apply Euler eho, he sochasic inegral in 39 need o conver ino Io inegral. The sep size of Euler ehod for solving boh 39 4 is.. Figs. 3 show he nuerical soluion of he displaceen x he velociy ẋ respecively, corresponding o he pah shown in Fig.. By coparing Fig. wih 3, i is ineresing o see ha while here are jups for he velociy, here is no jups for he displaceen. This is a consequence of equaion 4. Based on he nuerical soluions of x ẋ, as shown in Figs. 3, we

8 8 Xu Sun e al. can copue he energy increen E he work W K, which are defined as E W K x ẋ x ẋ, 4 gx, ẋẋs gx, ẋẋs N i fx, ẋẋs dls fx, ẋẋs dbs Ȳ i L i, 43 respecively, where L i cc i C i c C i, denoe inegrals in he Sraonovich sense, N is he nuber of jups upo ie, Ȳi L i is he soluion o he following ODE, d dλȳiλ fx i, Ȳiλ ẋ i Ȳiλ ẋ i, Ȳ i. 44 wih λ aking value of λ L i for L i > or L i λ for L i <. The resuls of E W K are copared in Fig. 4. For convenience of coparison, par of he daa in Fig. 4 for ie.,.4,.6,.8 are lised in Table. As shown in Fig. 4 or Table, he energy increen E appears o agree well wih he work W K. The difference beween E W K is ainly due o he runcaion error caused by Euler ehod, which has accuracy of order in copuing sochasic inegral wih respec o brownian oion 6, where is he sep size, as saed earlier. Noe ha any eho such as Milsein ehod, are available o copue he sochasic inegral wih high order accuracy 6. However, hese eho are ou of he scope of his paper will no be used here. Case In his case, 4 or is inerpreed by using Io sochasic inegrals. Now 39 4 becoe dx ẋ d dẋ k x d gx, ẋ d 45 b fx, ẋ db, respecively. In he siulaion, he driving process L all he siulaion paraeers are aken he sae as in case. Figures 5 6 presen he corresponding nuerical soluions of he displaceen velociy, respecively. Coparison of he energy increen, defined by 4, he work done, now defined by W K gx, ẋẋs b N i fx, ẋẋs dbs fxs, ẋs ẋs L i, 47 is presened in Fig. 7. Par of Daa in Fig. 7 for ie.,.4,.6,.8, are lised in Table. Noe ha all he curves in Fig. 7 end o have a very sall variance in he ie span.84 <. This is he consequence of he fac ha he velociy is very sall for.84 <, as shown in Fig. 6. Since fx, ẋ gx, ẋ ẋ, i follows fro 4, ha boh he energy increen he work change slowly for very sall velociy ẋ. Coparing Fig. 7 wih Fig. 4, Table wih Table, we can see ha wih he sae siulaion paraeers, he proposed sochasic inegral lea o uch s- aller difference beween he energy increen he corresponding work han is Io inegral counerpar, as can also be seen ore clearly fro Fig. 8, where he above wo differences are jus shown ogeher. This suggess ha he proposed inegral is a beer choice han Io inegral in order for he energy conservaion law o be saisfied in sochasic odeling under cobined Gaussian Poisson whie noise. { x i x i, ẋ i ẋ i fxs, ẋs L i, 46

9 Sochasic odeling of nonlinear oscillaors under cobined Gaussian Poisson Whie noise 9 L Tie Fig. A saple pah of he driving process L as a cobinaion of a Gaussian process a copound Poisson process given in 3. Velociy Tie Fig. 3 The evoluion of he velociy ẋ as he soluion of Duffing-van der Pol equaion 4 defined by he proposed inegral 7 34, where he driving process L is given in Fig.. 8 Increen of Energy Work Displaceen.5 Magniude Tie Fig. The evoluion of he displaceen x as he soluion of Duffing-van der Pol equaion 4 defined by he proposed inegral 7 34, where he driving process L is given in Fig Tie Fig. 4 Coparison of he change in oal energy, defined by 4, he work done by he force, defined by 43, where he proposed inegral 7 34 is used. Table Energy increen E vs. he work W K for he case wih he proposed inegral, where he Err is defined as he difference beween E W K ie E W K Err

10 Xu Sun e al Increen of Energy Work Displaceen.4 Magniude Tie Fig. 5 The evoluion of he displaceen x as he soluion of Duffing-van der Pol equaion 4 defined by Io inegral, where he driving process L is given in Fig Tie Fig. 7 Coparison of he change in oal energy, defined by 4, he work done by he force, defined by 47, where Io inegral is used..5.5 for he proposed inegral for Io inegral.5 Velociy.5.5 Err Tie Fig. 6 The evoluion of he velociy ẋ as he soluion of Duffing-van der Pol equaion 4 defined by Io inegral, where he driving process L is given in Fig Tie Fig. 8 Coparison of he difference beween he energy increen he work for cases wih he proposed inegral Io inegral, respecively. Table Energy increen E vs. he work W K for he case wih Io inegral, where he Err is defined as he difference beween E W K ie E W K Err

11 Sochasic odeling of nonlinear oscillaors under cobined Gaussian Poisson Whie noise 5 Conclusion We consider sochasic differenial equaion odels of nonlinear oscillaors under exciaions of cobined Gaussian Poisson whie noise. Since any differen ypes of sochasic inegral can be defined o inerpre soluions of sochasic differenial equaions, i is desirable o know which sochasic inegral is ore relaed o physical realiy. To his end, we inroduce a sochasic inegral which is defined such ha he energy conservaion law is saisfied. The relaionship of his sochasic inegral he well known DiPaola-Falsone inegral is discussed. I urns ou ha he forer is consisen wih he laer, bu copared o he laer, he forer is applicable under ore general condiions. We poin ou ha here are no absolue bes ways in choosing aong sochasic inegrals, i depen on specific applicaion. The proposed sochasic inegrals are ore appropriae in physics such as echanical syses while he Io inegral is ore suiable in finance applicaions. We will furher explore applicaions of he proposed sochasic inegral in our fuure work. Appendix: Proof of he energy-work law 33 fro he soluion 3 For convenience, we inroduce he following noaions: gs gxs, ẋs, fs fxs, ẋs, fẋs f ẋsxs, ẋs. In his Appendix, all s- ochasic inegrals wih respec o Brownian oion are in he sense of Io we have dropped noaion. Then he energy-work law 33 is equivalen o h side of 48, we ge sin ω s gs fsf ẋs LHS sinω sfs dbs cos ω s gs fsf ẋs cosω sfs dbs ω cosωx sinωẋ sin ω s gs fsf ẋs ω cosωx sinωẋ sin ω s gs fsf ẋs sinω sfs dbs sinω sfs dbs ω sinωx cosωẋ cos ω s gs fsf ẋs ω sinωx cosωẋ cosω s gs fsf ẋs cosω sfs dbs cosω sfs dbs. 49 Subsiuing 3 ino he righ-h side of 48, we ge ẋ ω x ẋ ω x gs fsf ẋs ẋs f s fsẋs dbs. 48 Nex, we show he soluion given in 3 saisfies he energy-work law 48. Denoe he righ lef h sides of 48 by RHS LHS, respecively. Subsiue 3 ino he lef RHS s s s s gs fsfẋs ω sinωsx cosωsẋ cosωs p gs fsf ẋs gp fpf ẋp cosωs p dp gs fsf ẋs fp dbp f s fs ω sinωsx cosωsẋ dbs cosωs pfs gp fpf ẋp dp dbs cosωs pfsfp dbp dbs. 5

12 Xu Sun e al. To prove LHS in 49 is equal o RHS in 5, we clai he following facs s s cosωs p gs fsf ẋs gp fpf ẋp dp sinω s gs fsf ẋs cosω s gs fsf ẋs cosωs pfsfp dbp dbs, 5 f s sinω sfs dbs cosω sfs dbs, 5 s s cosωs p gs fsf ẋs cosωs p gp fpf ẋp cosω s gs fsf ẋs fp dbp cosω sfs dbs sinω s gs fsf ẋs fs dp dbs sinω sfs dbs 53 gs fsf ẋs ω sinωsx cosωsẋ ω sinωx cosωẋ cosω s gs fsf ẋs ω cosωx sinωẋ sinω s gs fsf ẋs, 54 fs ω sinωsx cosωsẋ dbs ω sinωx cosωẋ ω cosωx sinωẋ cosω sfs dbs sinω sfs dbs. 55 One can easily see ha are rue by using he rignoeric ideniies cosωs cosω cosω s sinω sinω s, sinωs sinω cosω s cosω sinω s, In he following, we give he proofs for 5 5. The proof of 53 is siilar o hose for 5 5 is no given here. To prove 5 is rue, we rewrie he righ-h side of 5 as double inegrals sinω s gs fsf ẋs cosω s gs fsf ẋs sinω p sinω s gs fsf ẋs dp s cosω p cosω s gp fpf ẋp gs fsf ẋs dp cosωs p gp fpf ẋp gs fsf ẋs dp cosωs p gp fpf ẋp gs fsf ẋs dp. gp fpf ẋp Siilarly, o prove 5, we rewrie he righ-h side 5 as sinω sfs dbs cosω sfs dbs cosωs pfsfp dbp dbs. 56

13 Sochasic odeling of nonlinear oscillaors under cobined Gaussian Poisson Whie noise 3 The inegral doain for he righ-h side of 56 is a square given by A {s, p s,, p, }. Decopose he square ino hree pars: A {s, p s < p }, A {s, p p < s }, A 3 {s, s s }, hen he righ-h side of 56 becoes cosωs pfsfp dbp dbs A A A 3 cosωs pfsfp dbp dbs. 57 Noe ha cosωs pfsfp dbp dbs A cosωs pfsfp dbp dbs A s cosωs pfsfp dbp dbs, 58 A 3 cosωs pfsfp dbp dbs f s. 59 I follows fro ha 5 is rue. Add Eqs. 5 o 55, we ge LHS RHS, hence 33 is proved. References. B. K. Oksendal. Sochasic Differenial Equaions : an Inroducion wih Applicaions. Springer, 6h Ediion, 3.. F. C. Klebaner. Inroducion o sochasic calculus wih applicaions. nd Ediion, Iperial College Press, H. T. Zhu. Muliple-peak probabiliy densiy funcion of non-linear oscillaors under gaussian whie noise. Probabilisic Engineering Mechanics, 3:46 5, Z. H. Zhao, K. Chang, J. J. Neio. Asypoic behavior of soluions o absrac sochasic fracional parial inegrodifferenial equaions. Absrac Applied Analysis, 3:3886, G. Luo, J. Liang, C. Zhu. The ransversal hooclinic soluions chaos for sochasic ordinary differenial equaions. Journal of Maheaical Analysis Applicaions, 4:3 35, E. Wong M. Zakai. On he relaion beween ordinary sochasic differenial equaions. Inernaional Journal of Engineering Science, 3:3 9, R. A. Ibrahi. Paraeric Ro Vibraion. Research Sudies Press, Y. Yong Y. K. Lin. Exac saionary response soluion for second order nonlinear syses under paraeric exernal whie noise exciaions. Journal of Applied Mechanics, Transacions of he Aerican Sociey of Mechanical Engineers, 54:44 48, J. Shi, T. Chen, R. Yuan, P. Ao. Relaion of a new inerpreaion of sochasic differenial equaions o io process. Journal of Saisical physics, 48:579 59,.. R. Yuan P. Ao. Beyond io versus sraonovich. Journal of Saisical Mechanics, page P7,.. M. Volpe, L. Helden, T. Breschneider, J. Wehr, C. Bechinger. Influence of noise on force easureen. Physcial review leers, 4:76,.. M. Di Paola G. Falsone. Io sraonovich inegrals for dela-correlaed processes. Probabilisic engineering echanics, 8:97 8, M. Di Paola G. Falsone. Sochasic dynaics of non-linear syses driven by non-noral dela-correlaed processes. ASME Journal of applied echanics, 6:4 48, S. Caddei M. Di Paola. Ideal physical whie noise in sochasic analysis. Inernaional Journal of Non-linear Mechanics, 35:58 59, C. Proppe. The wong-zakai heore for dynaical syses wih paraeric poisson whie noise exciaion. Inernaional Journal of Engineering science, 4:65 78, M. Di Paola A. Pirroa. Direc derivaion of correcive ers in sde hrough nonlinear ransforaion on fokker-planck equaion. Nonlinear Dynaics, 36:349 36, A. Pirroa. Non-linear syses under paraeric whie noise inpu: Digial siulaion response. Inernaional Journal of Non-linear Mechanics, 4:88, A. Pirroa. Muliplicaive cases fro addiive cases: Exension of kologorov-feller equaion o paraeric poisson whie noise processes. Probabilisic engineering echanics, :7 35, Y. Zeng W. Q. Zhu. Sochasic averaging of quasilinear syses driven by poisson whie noise. Probabilisic engineering echanics, 5:99 7,.. Y. Zeng W. Q. Zhu. Sochasic averaging of n- diensional non-linear dynaical syses subjec o non-gaussian wide-b ro exciaions. Inernaional Journal of Non-linear Mechanics, 45:57 586,.. J. Wan W. Zhu. Sochasic averaging of quasiinegrable non-resonan hailonian syses under cobined gaussian poisson whie noise exciaions. Nonlinear Dynaics, 76:7 89, 4.. W. Liu, W. Zhu, W. Jia. Sochasic sabiliy of quasiinegrable non-resonan hailonian syses under paraeric exciaions of cobined gaussian poisson whie noises. Inernaional journal of non-linear Mechanics, 58:9 98, M. Grigoriu. The io sraonovich inegrals for s- ochasic differenial equaions wih poisson whie noise. Probabilisic engineering echanics, 3:75 8, S. L. J. Hu. Closure on discussion by di paola,. falsone, g., on response of dynaic syses excied by non-gaussian pulse processes. ASCE Journal of engineering echanics, :47 474, X. Sun, J. Duan, X. Li. An alernaive expression for sochasic dynaical syses wih paraeric poisson

14 4 Xu Sun e al. whie noise. Probabilisic Engineering Mechanics, 3: 4, P. Kloeden E. Plaen. Nuerical Soluions of S- ochasic differenial equaions. Springer, 99.

Introduction to Numerical Analysis. In this lesson you will be taken through a pair of techniques that will be used to solve the equations of.

Introduction to Numerical Analysis. In this lesson you will be taken through a pair of techniques that will be used to solve the equations of. Inroducion o Nuerical Analysis oion In his lesson you will be aen hrough a pair of echniques ha will be used o solve he equaions of and v dx d a F d for siuaions in which F is well nown, and he iniial

More information

Homework 2 Solutions

Homework 2 Solutions Mah 308 Differenial Equaions Fall 2002 & 2. See he las page. Hoework 2 Soluions 3a). Newon s secon law of oion says ha a = F, an we know a =, so we have = F. One par of he force is graviy, g. However,

More information

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals

More information

TIME DELAY BASEDUNKNOWN INPUT OBSERVER DESIGN FOR NETWORK CONTROL SYSTEM

TIME DELAY BASEDUNKNOWN INPUT OBSERVER DESIGN FOR NETWORK CONTROL SYSTEM TIME DELAY ASEDUNKNOWN INPUT OSERVER DESIGN FOR NETWORK CONTROL SYSTEM Siddhan Chopra J.S. Laher Elecrical Engineering Deparen NIT Kurukshera (India Elecrical Engineering Deparen NIT Kurukshera (India

More information

7 The Itô/Stratonovich dilemma

7 The Itô/Stratonovich dilemma 7 The Iô/Sraonovich dilemma The dilemma: wha does he idealizaion of dela-funcion-correlaed noise mean? ẋ = f(x) + g(x)η() η()η( ) = κδ( ). (1) Previously, we argued by a limiing procedure: aking noise

More information

Wave Mechanics. January 16, 2017

Wave Mechanics. January 16, 2017 Wave Mechanics January 6, 7 The ie-dependen Schrödinger equaion We have seen how he ie-dependen Schrodinger equaion, Ψ + Ψ i Ψ follows as a non-relaivisic version of he Klein-Gordon equaion. In wave echanics,

More information

Chapter 2. First Order Scalar Equations

Chapter 2. First Order Scalar Equations Chaper. Firs Order Scalar Equaions We sar our sudy of differenial equaions in he same way he pioneers in his field did. We show paricular echniques o solve paricular ypes of firs order differenial equaions.

More information

Fourier Series & The Fourier Transform. Joseph Fourier, our hero. Lord Kelvin on Fourier s theorem. What do we want from the Fourier Transform?

Fourier Series & The Fourier Transform. Joseph Fourier, our hero. Lord Kelvin on Fourier s theorem. What do we want from the Fourier Transform? ourier Series & The ourier Transfor Wha is he ourier Transfor? Wha do we wan fro he ourier Transfor? We desire a easure of he frequencies presen in a wave. This will lead o a definiion of he er, he specru.

More information

arxiv: v1 [math.ca] 15 Nov 2016

arxiv: v1 [math.ca] 15 Nov 2016 arxiv:6.599v [mah.ca] 5 Nov 26 Counerexamples on Jumarie s hree basic fracional calculus formulae for non-differeniable coninuous funcions Cheng-shi Liu Deparmen of Mahemaics Norheas Peroleum Universiy

More information

Some Basic Information about M-S-D Systems

Some Basic Information about M-S-D Systems Some Basic Informaion abou M-S-D Sysems 1 Inroducion We wan o give some summary of he facs concerning unforced (homogeneous) and forced (non-homogeneous) models for linear oscillaors governed by second-order,

More information

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes Half-Range Series 2.5 Inroducion In his Secion we address he following problem: Can we find a Fourier series expansion of a funcion defined over a finie inerval? Of course we recognise ha such a funcion

More information

10. State Space Methods

10. State Space Methods . Sae Space Mehods. Inroducion Sae space modelling was briefly inroduced in chaper. Here more coverage is provided of sae space mehods before some of heir uses in conrol sysem design are covered in he

More information

2. Nonlinear Conservation Law Equations

2. Nonlinear Conservation Law Equations . Nonlinear Conservaion Law Equaions One of he clear lessons learned over recen years in sudying nonlinear parial differenial equaions is ha i is generally no wise o ry o aack a general class of nonlinear

More information

8. Basic RL and RC Circuits

8. Basic RL and RC Circuits 8. Basic L and C Circuis This chaper deals wih he soluions of he responses of L and C circuis The analysis of C and L circuis leads o a linear differenial equaion This chaper covers he following opics

More information

Variational Iteration Method for Solving System of Fractional Order Ordinary Differential Equations

Variational Iteration Method for Solving System of Fractional Order Ordinary Differential Equations IOSR Journal of Mahemaics (IOSR-JM) e-issn: 2278-5728, p-issn: 2319-765X. Volume 1, Issue 6 Ver. II (Nov - Dec. 214), PP 48-54 Variaional Ieraion Mehod for Solving Sysem of Fracional Order Ordinary Differenial

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution

Physics 127b: Statistical Mechanics. Fokker-Planck Equation. Time Evolution Physics 7b: Saisical Mechanics Fokker-Planck Equaion The Langevin equaion approach o he evoluion of he velociy disribuion for he Brownian paricle migh leave you uncomforable. A more formal reamen of his

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

Lecture 23 Damped Motion

Lecture 23 Damped Motion Differenial Equaions (MTH40) Lecure Daped Moion In he previous lecure, we discussed he free haronic oion ha assues no rearding forces acing on he oving ass. However No rearding forces acing on he oving

More information

THE FINITE HAUSDORFF AND FRACTAL DIMENSIONS OF THE GLOBAL ATTRACTOR FOR A CLASS KIRCHHOFF-TYPE EQUATIONS

THE FINITE HAUSDORFF AND FRACTAL DIMENSIONS OF THE GLOBAL ATTRACTOR FOR A CLASS KIRCHHOFF-TYPE EQUATIONS European Journal of Maheaics and Copuer Science Vol 4 No 7 ISSN 59-995 HE FINIE HAUSDORFF AND FRACAL DIMENSIONS OF HE GLOBAL ARACOR FOR A CLASS KIRCHHOFF-YPE EQUAIONS Guoguang Lin & Xiangshuang Xia Deparen

More information

Stability and Bifurcation in a Neural Network Model with Two Delays

Stability and Bifurcation in a Neural Network Model with Two Delays Inernaional Mahemaical Forum, Vol. 6, 11, no. 35, 175-1731 Sabiliy and Bifurcaion in a Neural Nework Model wih Two Delays GuangPing Hu and XiaoLing Li School of Mahemaics and Physics, Nanjing Universiy

More information

t 2 B F x,t n dsdt t u x,t dxdt

t 2 B F x,t n dsdt t u x,t dxdt Evoluion Equaions For 0, fixed, le U U0, where U denoes a bounded open se in R n.suppose ha U is filled wih a maerial in which a conaminan is being ranspored by various means including diffusion and convecion.

More information

2.1 Harmonic excitation of undamped systems

2.1 Harmonic excitation of undamped systems 2.1 Haronic exciaion of undaped syses Sanaoja 2_1.1 2.1 Haronic exciaion of undaped syses (Vaienaaoan syseein haroninen heräe) The following syse is sudied: y x F() Free-body diagra f x g x() N F() In

More information

Application of Homotopy Analysis Method for Solving various types of Problems of Partial Differential Equations

Application of Homotopy Analysis Method for Solving various types of Problems of Partial Differential Equations Applicaion of Hooopy Analysis Mehod for olving various ypes of Probles of Parial Differenial Equaions V.P.Gohil, Dr. G. A. anabha,assisan Professor, Deparen of Maheaics, Governen Engineering College, Bhavnagar,

More information

6.2 Transforms of Derivatives and Integrals.

6.2 Transforms of Derivatives and Integrals. SEC. 6.2 Transforms of Derivaives and Inegrals. ODEs 2 3 33 39 23. Change of scale. If l( f ()) F(s) and c is any 33 45 APPLICATION OF s-shifting posiive consan, show ha l( f (c)) F(s>c)>c (Hin: In Probs.

More information

On the approximation of particular solution of nonhomogeneous linear differential equation with Legendre series

On the approximation of particular solution of nonhomogeneous linear differential equation with Legendre series The Journal of Applied Science Vol. 5 No. : -9 [6] วารสารว ทยาศาสตร ประย กต doi:.446/j.appsci.6.8. ISSN 53-785 Prined in Thailand Research Aricle On he approxiaion of paricular soluion of nonhoogeneous

More information

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3

d 1 = c 1 b 2 - b 1 c 2 d 2 = c 1 b 3 - b 1 c 3 and d = c b - b c c d = c b - b c c This process is coninued unil he nh row has been compleed. The complee array of coefficiens is riangular. Noe ha in developing he array an enire row may be divided or

More information

Vehicle Arrival Models : Headway

Vehicle Arrival Models : Headway Chaper 12 Vehicle Arrival Models : Headway 12.1 Inroducion Modelling arrival of vehicle a secion of road is an imporan sep in raffic flow modelling. I has imporan applicaion in raffic flow simulaion where

More information

Most Probable Phase Portraits of Stochastic Differential Equations and Its Numerical Simulation

Most Probable Phase Portraits of Stochastic Differential Equations and Its Numerical Simulation Mos Probable Phase Porrais of Sochasic Differenial Equaions and Is Numerical Simulaion Bing Yang, Zhu Zeng and Ling Wang 3 School of Mahemaics and Saisics, Huazhong Universiy of Science and Technology,

More information

LAPLACE TRANSFORM AND TRANSFER FUNCTION

LAPLACE TRANSFORM AND TRANSFER FUNCTION CHBE320 LECTURE V LAPLACE TRANSFORM AND TRANSFER FUNCTION Professor Dae Ryook Yang Spring 2018 Dep. of Chemical and Biological Engineering 5-1 Road Map of he Lecure V Laplace Transform and Transfer funcions

More information

Fractional Method of Characteristics for Fractional Partial Differential Equations

Fractional Method of Characteristics for Fractional Partial Differential Equations Fracional Mehod of Characerisics for Fracional Parial Differenial Equaions Guo-cheng Wu* Modern Teile Insiue, Donghua Universiy, 188 Yan-an ilu Road, Shanghai 51, PR China Absrac The mehod of characerisics

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

Predator - Prey Model Trajectories and the nonlinear conservation law

Predator - Prey Model Trajectories and the nonlinear conservation law Predaor - Prey Model Trajecories and he nonlinear conservaion law James K. Peerson Deparmen of Biological Sciences and Deparmen of Mahemaical Sciences Clemson Universiy Ocober 28, 213 Ouline Drawing Trajecories

More information

6. Stochastic calculus with jump processes

6. Stochastic calculus with jump processes A) Trading sraegies (1/3) Marke wih d asses S = (S 1,, S d ) A rading sraegy can be modelled wih a vecor φ describing he quaniies invesed in each asse a each insan : φ = (φ 1,, φ d ) The value a of a porfolio

More information

The Asymptotic Behavior of Nonoscillatory Solutions of Some Nonlinear Dynamic Equations on Time Scales

The Asymptotic Behavior of Nonoscillatory Solutions of Some Nonlinear Dynamic Equations on Time Scales Advances in Dynamical Sysems and Applicaions. ISSN 0973-5321 Volume 1 Number 1 (2006, pp. 103 112 c Research India Publicaions hp://www.ripublicaion.com/adsa.hm The Asympoic Behavior of Nonoscillaory Soluions

More information

M x t = K x F t x t = A x M 1 F t. M x t = K x cos t G 0. x t = A x cos t F 0

M x t = K x F t x t = A x M 1 F t. M x t = K x cos t G 0. x t = A x cos t F 0 Forced oscillaions (sill undaped): If he forcing is sinusoidal, M = K F = A M F M = K cos G wih F = M G = A cos F Fro he fundaenal heore for linear ransforaions we now ha he general soluion o his inhoogeneous

More information

The expectation value of the field operator.

The expectation value of the field operator. The expecaion value of he field operaor. Dan Solomon Universiy of Illinois Chicago, IL dsolom@uic.edu June, 04 Absrac. Much of he mahemaical developmen of quanum field heory has been in suppor of deermining

More information

Thermal Forces and Brownian Motion

Thermal Forces and Brownian Motion Theral Forces and Brownian Moion Ju Li GEM4 Suer School 006 Cell and Molecular Mechanics in BioMedicine Augus 7 18, 006, MIT, Cabridge, MA, USA Ouline Meaning of he Cenral Lii Theore Diffusion vs Langevin

More information

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is

( ) ( ) if t = t. It must satisfy the identity. So, bulkiness of the unit impulse (hyper)function is equal to 1. The defining characteristic is UNIT IMPULSE RESPONSE, UNIT STEP RESPONSE, STABILITY. Uni impulse funcion (Dirac dela funcion, dela funcion) rigorously defined is no sricly a funcion, bu disribuion (or measure), precise reamen requires

More information

A Generalization of Student s t-distribution from the Viewpoint of Special Functions

A Generalization of Student s t-distribution from the Viewpoint of Special Functions A Generalizaion of Suden s -disribuion fro he Viewpoin of Special Funcions WOLFRAM KOEPF and MOHAMMAD MASJED-JAMEI Deparen of Maheaics, Universiy of Kassel, Heinrich-Ple-Sr. 4, D-343 Kassel, Gerany Deparen

More information

Problem set 2 for the course on. Markov chains and mixing times

Problem set 2 for the course on. Markov chains and mixing times J. Seif T. Hirscher Soluions o Proble se for he course on Markov chains and ixing ies February 7, 04 Exercise 7 (Reversible chains). (i) Assue ha we have a Markov chain wih ransiion arix P, such ha here

More information

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles

Diebold, Chapter 7. Francis X. Diebold, Elements of Forecasting, 4th Edition (Mason, Ohio: Cengage Learning, 2006). Chapter 7. Characterizing Cycles Diebold, Chaper 7 Francis X. Diebold, Elemens of Forecasing, 4h Ediion (Mason, Ohio: Cengage Learning, 006). Chaper 7. Characerizing Cycles Afer compleing his reading you should be able o: Define covariance

More information

Testing for a Single Factor Model in the Multivariate State Space Framework

Testing for a Single Factor Model in the Multivariate State Space Framework esing for a Single Facor Model in he Mulivariae Sae Space Framework Chen C.-Y. M. Chiba and M. Kobayashi Inernaional Graduae School of Social Sciences Yokohama Naional Universiy Japan Faculy of Economics

More information

Solution of Integro-Differential Equations by Using ELzaki Transform

Solution of Integro-Differential Equations by Using ELzaki Transform Global Journal of Mahemaical Sciences: Theory and Pracical. Volume, Number (), pp. - Inernaional Research Publicaion House hp://www.irphouse.com Soluion of Inegro-Differenial Equaions by Using ELzaki Transform

More information

An Introduction to Malliavin calculus and its applications

An Introduction to Malliavin calculus and its applications An Inroducion o Malliavin calculus and is applicaions Lecure 5: Smoohness of he densiy and Hörmander s heorem David Nualar Deparmen of Mahemaics Kansas Universiy Universiy of Wyoming Summer School 214

More information

Thus the force is proportional but opposite to the displacement away from equilibrium.

Thus the force is proportional but opposite to the displacement away from equilibrium. Chaper 3 : Siple Haronic Moion Hooe s law saes ha he force (F) eered by an ideal spring is proporional o is elongaion l F= l where is he spring consan. Consider a ass hanging on a he spring. In equilibriu

More information

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t

Hamilton- J acobi Equation: Explicit Formulas In this lecture we try to apply the method of characteristics to the Hamilton-Jacobi equation: u t M ah 5 2 7 Fall 2 0 0 9 L ecure 1 0 O c. 7, 2 0 0 9 Hamilon- J acobi Equaion: Explici Formulas In his lecure we ry o apply he mehod of characerisics o he Hamilon-Jacobi equaion: u + H D u, x = 0 in R n

More information

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon

3.1.3 INTRODUCTION TO DYNAMIC OPTIMIZATION: DISCRETE TIME PROBLEMS. A. The Hamiltonian and First-Order Conditions in a Finite Time Horizon 3..3 INRODUCION O DYNAMIC OPIMIZAION: DISCREE IME PROBLEMS A. he Hamilonian and Firs-Order Condiions in a Finie ime Horizon Define a new funcion, he Hamilonian funcion, H. H he change in he oal value of

More information

Properties Of Solutions To A Generalized Liénard Equation With Forcing Term

Properties Of Solutions To A Generalized Liénard Equation With Forcing Term Applied Mahemaics E-Noes, 8(28), 4-44 c ISSN 67-25 Available free a mirror sies of hp://www.mah.nhu.edu.w/ amen/ Properies Of Soluions To A Generalized Liénard Equaion Wih Forcing Term Allan Kroopnick

More information

Stochastic Model for Cancer Cell Growth through Single Forward Mutation

Stochastic Model for Cancer Cell Growth through Single Forward Mutation Journal of Modern Applied Saisical Mehods Volume 16 Issue 1 Aricle 31 5-1-2017 Sochasic Model for Cancer Cell Growh hrough Single Forward Muaion Jayabharahiraj Jayabalan Pondicherry Universiy, jayabharahi8@gmail.com

More information

Higher Order Difference Schemes for Heat Equation

Higher Order Difference Schemes for Heat Equation Available a p://pvau.edu/aa Appl. Appl. Ma. ISSN: 9-966 Vol., Issue (Deceber 009), pp. 6 7 (Previously, Vol., No. ) Applicaions and Applied Maeaics: An Inernaional Journal (AAM) Higer Order Difference

More information

Solutions to Assignment 1

Solutions to Assignment 1 MA 2326 Differenial Equaions Insrucor: Peronela Radu Friday, February 8, 203 Soluions o Assignmen. Find he general soluions of he following ODEs: (a) 2 x = an x Soluion: I is a separable equaion as we

More information

15. Vector Valued Functions

15. Vector Valued Functions 1. Vecor Valued Funcions Up o his poin, we have presened vecors wih consan componens, for example, 1, and,,4. However, we can allow he componens of a vecor o be funcions of a common variable. For example,

More information

Lecture 18 GMM:IV, Nonlinear Models

Lecture 18 GMM:IV, Nonlinear Models Lecure 8 :IV, Nonlinear Models Le Z, be an rx funcion of a kx paraeer vecor, r > k, and a rando vecor Z, such ha he r populaion oen condiions also called esiain equaions EZ, hold for all, where is he rue

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Linear Response Theory: The connecion beween QFT and experimens 3.1. Basic conceps and ideas Q: How do we measure he conduciviy of a meal? A: we firs inroduce a weak elecric field E, and

More information

ψ(t) = V x (0)V x (t)

ψ(t) = V x (0)V x (t) .93 Home Work Se No. (Professor Sow-Hsin Chen Spring Term 5. Due March 7, 5. This problem concerns calculaions of analyical expressions for he self-inermediae scaering funcion (ISF of he es paricle in

More information

Math 334 Fall 2011 Homework 11 Solutions

Math 334 Fall 2011 Homework 11 Solutions Dec. 2, 2 Mah 334 Fall 2 Homework Soluions Basic Problem. Transform he following iniial value problem ino an iniial value problem for a sysem: u + p()u + q() u g(), u() u, u () v. () Soluion. Le v u. Then

More information

4.6 One Dimensional Kinematics and Integration

4.6 One Dimensional Kinematics and Integration 4.6 One Dimensional Kinemaics and Inegraion When he acceleraion a( of an objec is a non-consan funcion of ime, we would like o deermine he ime dependence of he posiion funcion x( and he x -componen of

More information

Chapter 9 Sinusoidal Steady State Analysis

Chapter 9 Sinusoidal Steady State Analysis Chaper 9 Sinusoidal Seady Sae Analysis 9.-9. The Sinusoidal Source and Response 9.3 The Phasor 9.4 pedances of Passive Eleens 9.5-9.9 Circui Analysis Techniques in he Frequency Doain 9.0-9. The Transforer

More information

20. Applications of the Genetic-Drift Model

20. Applications of the Genetic-Drift Model 0. Applicaions of he Geneic-Drif Model 1) Deermining he probabiliy of forming any paricular combinaion of genoypes in he nex generaion: Example: If he parenal allele frequencies are p 0 = 0.35 and q 0

More information

Inequality measures for intersecting Lorenz curves: an alternative weak ordering

Inequality measures for intersecting Lorenz curves: an alternative weak ordering h Inernaional Scienific Conference Financial managemen of Firms and Financial Insiuions Osrava VŠB-TU of Osrava, Faculy of Economics, Deparmen of Finance 7 h 8 h Sepember 25 Absrac Inequaliy measures for

More information

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 13, Number 1/2012, pp

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 13, Number 1/2012, pp THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volue, Nuber /0, pp 4 SOLITON PERTURBATION THEORY FOR THE GENERALIZED KLEIN-GORDON EQUATION WITH FULL NONLINEARITY

More information

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities: Mah 4 Eam Review Problems Problem. Calculae he 3rd Taylor polynomial for arcsin a =. Soluion. Le f() = arcsin. For his problem, we use he formula f() + f () + f ()! + f () 3! for he 3rd Taylor polynomial

More information

9231 FURTHER MATHEMATICS

9231 FURTHER MATHEMATICS CAMBRIDGE INTERNATIONAL EXAMINATIONS GCE Advanced Level MARK SCHEME for he May/June series 9 FURTHER MATHEMATICS 9/ Paper, maximum raw mark This mark scheme is published as an aid o eachers and candidaes,

More information

THE APPROXIMATE AND EXACT SOLUTIONS OF THE SPACE- AND TIME-FRACTIONAL BURGERS EQUATIONS

THE APPROXIMATE AND EXACT SOLUTIONS OF THE SPACE- AND TIME-FRACTIONAL BURGERS EQUATIONS IJRRAS () June Kurulay Soluions of he Space & Tie-Fracional Burgers Equaions THE APPROXIMATE AND EXACT SOLUTIONS OF THE SPACE- AND TIME-FRACTIONAL BURGERS EQUATIONS Muhae Kurulay Yildiz Technical Uniersiy

More information

ACE 562 Fall Lecture 4: Simple Linear Regression Model: Specification and Estimation. by Professor Scott H. Irwin

ACE 562 Fall Lecture 4: Simple Linear Regression Model: Specification and Estimation. by Professor Scott H. Irwin ACE 56 Fall 005 Lecure 4: Simple Linear Regression Model: Specificaion and Esimaion by Professor Sco H. Irwin Required Reading: Griffihs, Hill and Judge. "Simple Regression: Economic and Saisical Model

More information

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation:

Hamilton- J acobi Equation: Weak S olution We continue the study of the Hamilton-Jacobi equation: M ah 5 7 Fall 9 L ecure O c. 4, 9 ) Hamilon- J acobi Equaion: Weak S oluion We coninue he sudy of he Hamilon-Jacobi equaion: We have shown ha u + H D u) = R n, ) ; u = g R n { = }. ). In general we canno

More information

A Note on the Equivalence of Fractional Relaxation Equations to Differential Equations with Varying Coefficients

A Note on the Equivalence of Fractional Relaxation Equations to Differential Equations with Varying Coefficients mahemaics Aricle A Noe on he Equivalence of Fracional Relaxaion Equaions o Differenial Equaions wih Varying Coefficiens Francesco Mainardi Deparmen of Physics and Asronomy, Universiy of Bologna, and he

More information

On a Fractional Stochastic Landau-Ginzburg Equation

On a Fractional Stochastic Landau-Ginzburg Equation Applied Mahemaical Sciences, Vol. 4, 1, no. 7, 317-35 On a Fracional Sochasic Landau-Ginzburg Equaion Nguyen Tien Dung Deparmen of Mahemaics, FPT Universiy 15B Pham Hung Sree, Hanoi, Vienam dungn@fp.edu.vn

More information

Class Meeting # 10: Introduction to the Wave Equation

Class Meeting # 10: Introduction to the Wave Equation MATH 8.5 COURSE NOTES - CLASS MEETING # 0 8.5 Inroducion o PDEs, Fall 0 Professor: Jared Speck Class Meeing # 0: Inroducion o he Wave Equaion. Wha is he wave equaion? The sandard wave equaion for a funcion

More information

CHAPTER 2 Signals And Spectra

CHAPTER 2 Signals And Spectra CHAPER Signals And Specra Properies of Signals and Noise In communicaion sysems he received waveform is usually caegorized ino he desired par conaining he informaion, and he undesired par. he desired par

More information

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n

Module 2 F c i k c s la l w a s o s f dif di fusi s o i n Module Fick s laws of diffusion Fick s laws of diffusion and hin film soluion Adolf Fick (1855) proposed: d J α d d d J (mole/m s) flu (m /s) diffusion coefficien and (mole/m 3 ) concenraion of ions, aoms

More information

An Invariance for (2+1)-Extension of Burgers Equation and Formulae to Obtain Solutions of KP Equation

An Invariance for (2+1)-Extension of Burgers Equation and Formulae to Obtain Solutions of KP Equation Commun Theor Phys Beijing, China 43 2005 pp 591 596 c Inernaional Academic Publishers Vol 43, No 4, April 15, 2005 An Invariance for 2+1-Eension of Burgers Equaion Formulae o Obain Soluions of KP Equaion

More information

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k Challenge Problems DIS 03 and 0 March 6, 05 Choose one of he following problems, and work on i in your group. Your goal is o convince me ha your answer is correc. Even if your answer isn compleely correc,

More information

arxiv:quant-ph/ v1 5 Jul 2004

arxiv:quant-ph/ v1 5 Jul 2004 Numerical Mehods for Sochasic Differenial Equaions Joshua Wilkie Deparmen of Chemisry, Simon Fraser Universiy, Burnaby, Briish Columbia V5A 1S6, Canada Sochasic differenial equaions (sdes) play an imporan

More information

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still.

Lecture 2-1 Kinematics in One Dimension Displacement, Velocity and Acceleration Everything in the world is moving. Nothing stays still. Lecure - Kinemaics in One Dimension Displacemen, Velociy and Acceleraion Everyhing in he world is moving. Nohing says sill. Moion occurs a all scales of he universe, saring from he moion of elecrons in

More information

INDEX. Transient analysis 1 Initial Conditions 1

INDEX. Transient analysis 1 Initial Conditions 1 INDEX Secion Page Transien analysis 1 Iniial Condiions 1 Please inform me of your opinion of he relaive emphasis of he review maerial by simply making commens on his page and sending i o me a: Frank Mera

More information

MODULE 3 FUNCTION OF A RANDOM VARIABLE AND ITS DISTRIBUTION LECTURES PROBABILITY DISTRIBUTION OF A FUNCTION OF A RANDOM VARIABLE

MODULE 3 FUNCTION OF A RANDOM VARIABLE AND ITS DISTRIBUTION LECTURES PROBABILITY DISTRIBUTION OF A FUNCTION OF A RANDOM VARIABLE Topics MODULE 3 FUNCTION OF A RANDOM VARIABLE AND ITS DISTRIBUTION LECTURES 2-6 3. FUNCTION OF A RANDOM VARIABLE 3.2 PROBABILITY DISTRIBUTION OF A FUNCTION OF A RANDOM VARIABLE 3.3 EXPECTATION AND MOMENTS

More information

Oscillation Properties of a Logistic Equation with Several Delays

Oscillation Properties of a Logistic Equation with Several Delays Journal of Maheaical Analysis and Applicaions 247, 11 125 Ž 2. doi:1.16 jaa.2.683, available online a hp: www.idealibrary.co on Oscillaion Properies of a Logisic Equaion wih Several Delays Leonid Berezansy

More information

ENGI 9420 Engineering Analysis Assignment 2 Solutions

ENGI 9420 Engineering Analysis Assignment 2 Solutions ENGI 940 Engineering Analysis Assignmen Soluions 0 Fall [Second order ODEs, Laplace ransforms; Secions.0-.09]. Use Laplace ransforms o solve he iniial value problem [0] dy y, y( 0) 4 d + [This was Quesion

More information

Lecture #31, 32: The Ornstein-Uhlenbeck Process as a Model of Volatility

Lecture #31, 32: The Ornstein-Uhlenbeck Process as a Model of Volatility Saisics 441 (Fall 214) November 19, 21, 214 Prof Michael Kozdron Lecure #31, 32: The Ornsein-Uhlenbeck Process as a Model of Volailiy The Ornsein-Uhlenbeck process is a di usion process ha was inroduced

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

Morning Time: 1 hour 30 minutes Additional materials (enclosed):

Morning Time: 1 hour 30 minutes Additional materials (enclosed): ADVANCED GCE 78/0 MATHEMATICS (MEI) Differenial Equaions THURSDAY JANUARY 008 Morning Time: hour 30 minues Addiional maerials (enclosed): None Addiional maerials (required): Answer Bookle (8 pages) Graph

More information

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients

Section 3.5 Nonhomogeneous Equations; Method of Undetermined Coefficients Secion 3.5 Nonhomogeneous Equaions; Mehod of Undeermined Coefficiens Key Terms/Ideas: Linear Differenial operaor Nonlinear operaor Second order homogeneous DE Second order nonhomogeneous DE Soluion o homogeneous

More information

Harmonic oscillator in quantum mechanics

Harmonic oscillator in quantum mechanics Harmonic oscillaor in quanum mechanics PHYS400, Deparmen of Physics, Universiy of onnecicu hp://www.phys.uconn.edu/phys400/ Las modified: May, 05 Dimensionless Schrödinger s equaion in quanum mechanics

More information

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems.

Math Week 14 April 16-20: sections first order systems of linear differential equations; 7.4 mass-spring systems. Mah 2250-004 Week 4 April 6-20 secions 7.-7.3 firs order sysems of linear differenial equaions; 7.4 mass-spring sysems. Mon Apr 6 7.-7.2 Sysems of differenial equaions (7.), and he vecor Calculus we need

More information

On the Solutions of First and Second Order Nonlinear Initial Value Problems

On the Solutions of First and Second Order Nonlinear Initial Value Problems Proceedings of he World Congress on Engineering 13 Vol I, WCE 13, July 3-5, 13, London, U.K. On he Soluions of Firs and Second Order Nonlinear Iniial Value Problems Sia Charkri Absrac In his paper, we

More information

1 Widrow-Hoff Algorithm

1 Widrow-Hoff Algorithm COS 511: heoreical Machine Learning Lecurer: Rob Schapire Lecure # 18 Scribe: Shaoqing Yang April 10, 014 1 Widrow-Hoff Algorih Firs le s review he Widrow-Hoff algorih ha was covered fro las lecure: Algorih

More information

Recursive Least-Squares Fixed-Interval Smoother Using Covariance Information based on Innovation Approach in Linear Continuous Stochastic Systems

Recursive Least-Squares Fixed-Interval Smoother Using Covariance Information based on Innovation Approach in Linear Continuous Stochastic Systems 8 Froniers in Signal Processing, Vol. 1, No. 1, July 217 hps://dx.doi.org/1.2266/fsp.217.112 Recursive Leas-Squares Fixed-Inerval Smooher Using Covariance Informaion based on Innovaion Approach in Linear

More information

Riemann Hypothesis and Primorial Number. Choe Ryong Gil

Riemann Hypothesis and Primorial Number. Choe Ryong Gil Rieann Hyohesis Priorial Nuber Choe Ryong Gil Dearen of Maheaics Universiy of Sciences Gwahak- dong Unjong Disric Pyongyang DPRKorea Eail; ryonggilchoe@sar-conek Augus 8 5 Absrac; In his aer we consider

More information

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes

2.7. Some common engineering functions. Introduction. Prerequisites. Learning Outcomes Some common engineering funcions 2.7 Inroducion This secion provides a caalogue of some common funcions ofen used in Science and Engineering. These include polynomials, raional funcions, he modulus funcion

More information

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010

Simulation-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Simulaion-Solving Dynamic Models ABE 5646 Week 2, Spring 2010 Week Descripion Reading Maerial 2 Compuer Simulaion of Dynamic Models Finie Difference, coninuous saes, discree ime Simple Mehods Euler Trapezoid

More information

Boundedness and Exponential Asymptotic Stability in Dynamical Systems with Applications to Nonlinear Differential Equations with Unbounded Terms

Boundedness and Exponential Asymptotic Stability in Dynamical Systems with Applications to Nonlinear Differential Equations with Unbounded Terms Advances in Dynamical Sysems and Applicaions. ISSN 0973-531 Volume Number 1 007, pp. 107 11 Research India Publicaions hp://www.ripublicaion.com/adsa.hm Boundedness and Exponenial Asympoic Sabiliy in Dynamical

More information

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t...

t is a basis for the solution space to this system, then the matrix having these solutions as columns, t x 1 t, x 2 t,... x n t x 2 t... Mah 228- Fri Mar 24 5.6 Marix exponenials and linear sysems: The analogy beween firs order sysems of linear differenial equaions (Chaper 5) and scalar linear differenial equaions (Chaper ) is much sronger

More information

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions

Inventory Analysis and Management. Multi-Period Stochastic Models: Optimality of (s, S) Policy for K-Convex Objective Functions Muli-Period Sochasic Models: Opimali of (s, S) Polic for -Convex Objecive Funcions Consider a seing similar o he N-sage newsvendor problem excep ha now here is a fixed re-ordering cos (> 0) for each (re-)order.

More information

( ) = b n ( t) n " (2.111) or a system with many states to be considered, solving these equations isn t. = k U I ( t,t 0 )! ( t 0 ) (2.

( ) = b n ( t) n  (2.111) or a system with many states to be considered, solving these equations isn t. = k U I ( t,t 0 )! ( t 0 ) (2. Andrei Tokmakoff, MIT Deparmen of Chemisry, 3/14/007-6.4 PERTURBATION THEORY Given a Hamilonian H = H 0 + V where we know he eigenkes for H 0 : H 0 n = E n n, we can calculae he evoluion of he wavefuncion

More information

5. Stochastic processes (1)

5. Stochastic processes (1) Lec05.pp S-38.45 - Inroducion o Teleraffic Theory Spring 2005 Conens Basic conceps Poisson process 2 Sochasic processes () Consider some quaniy in a eleraffic (or any) sysem I ypically evolves in ime randomly

More information

EXERCISES FOR SECTION 1.5

EXERCISES FOR SECTION 1.5 1.5 Exisence and Uniqueness of Soluions 43 20. 1 v c 21. 1 v c 1 2 4 6 8 10 1 2 2 4 6 8 10 Graph of approximae soluion obained using Euler s mehod wih = 0.1. Graph of approximae soluion obained using Euler

More information

An Introduction to Backward Stochastic Differential Equations (BSDEs) PIMS Summer School 2016 in Mathematical Finance.

An Introduction to Backward Stochastic Differential Equations (BSDEs) PIMS Summer School 2016 in Mathematical Finance. 1 An Inroducion o Backward Sochasic Differenial Equaions (BSDEs) PIMS Summer School 2016 in Mahemaical Finance June 25, 2016 Chrisoph Frei cfrei@ualbera.ca This inroducion is based on Touzi [14], Bouchard

More information

Comparison between the Discrete and Continuous Time Models

Comparison between the Discrete and Continuous Time Models Comparison beween e Discree and Coninuous Time Models D. Sulsky June 21, 2012 1 Discree o Coninuous Recall e discree ime model Î = AIS Ŝ = S Î. Tese equaions ell us ow e populaion canges from one day o

More information