Predator Population Dynamics Involving Exponential Integral Function When Prey Follows Gompertz Model

Size: px
Start display at page:

Download "Predator Population Dynamics Involving Exponential Integral Function When Prey Follows Gompertz Model"

Transcription

1 Op Joral of Modllig ad Simlatio, 25, 3, 7-8 Pblishd Oli Jly 25 i SciRs. Prdator Poplatio Dyamics Ivolvig Expotial Itgral Fctio Wh Pry Follows Gomprtz Modl yl Tay Gosh *, Prachadra Rao Koya School of Mathmatical ad Statistical Scics, Hawassa Uivrsity, Hawassa, Ethiopia * ayl_tay@yahoo.com, drpraoccc@yahoo.co.i Rcivd 2 pril 25; accptd J 25; pblishd 5 J 25 Copyright 25 by athors ad Scitific Rsarch Pblishig Ic. This wor is licsd dr th Crativ Commos ttribtio Itratioal Lics (CC BY). bstract Th crrt stdy ivstigats th prdator-pry problm with assmptios that itractio of prdatio has a littl or o ffct o pry poplatio growth ad th pry s grow rat is tim dpdt. Th pry is assmd to follow th Gomprtz growth modl ad th rspctiv prdator growth fctio is costrctd by solvig ordiary diffrtial qatios. Th rslts show that th prdator poplatio modl is fod to b a fctio of th wll ow xpotial itgral fctio. Th soltio is also giv i Taylor s sris. Simlatio stdy shows that th prdator poplatio siz vtally covrgs ithr to a fiit positiv limit or zro or divrgs to positiv ifiity. Udr crtai coditios, th prdator poplatio covrgs to th asymptotic limit of th pry modl. Mor rslts ar icldd i th papr. Kywords Expotial Itgral Fctio, Gomprtz Modl, Poplatio Growth, Prdator, Pry. Itrodctio Th prdator-pry problm has b itrstig to may rsarchrs []-[7]. Modllig poplatio growth of itractig spcis ivolvs diffrtial qatios [] [2]. Th biological spcis itract i may ad complx ways that may affct th poplatio compositios ovr tim, d to atral or artificial or maagmt rasos. Prdatio ca icras, dcras, or hav littl ffct o th strgth, impact or importac of itrspcific comptitio [3]. Thy idicat that thr ar cass i which prdatio has vry littl ffct o comptitiv itractios. * Corrspodig athor. How to cit this papr: Gosh,.T. ad Koya, P.R. (25) Prdator Poplatio Dyamics Ivolvig Expotial Itgral Fctio Wh Pry Follows Gomprtz Modl. Op Joral of Modllig ad Simlatio, 3,

2 . T. Gosh, P. R. Koya It is discssd i [4] that th t ffcts of itrspcific spcis itractios o idividals ad poplatios vary i both sig (positiv, zro, gativ) ad magitd (strog to wa). Itractio otcoms ar cotxtdpdt wh th sig ad/or magitd chag as a fctio of th biotic or abiotic cotxt. Th prdator-pry problm with th assmptios of littl or o ffct of prdatio o th pry poplatio growth is stdid i [6] [7]. I this stdy, th pry poplatios ar assmd to grow accordig to logistic, Vo Brtalaffy ad Richards modls. Th rslts show that th prdatio affcts th prdator poplatio i sch a way that its growth ithr covrgs to a fiit positiv limit or to zro or divrgs to positiv ifiity. Thr ar svral optios to cosidr amog th gralizd growth modls [8]. Ths icld, for xampl, gralizd logistic, particlar cas of logistic, logistic, Richards, Vo Brtalaffy, Brody, Gomprtz, gralizd wibll, wibll, moomolclar, mitschrlich ad mor. Bhavior of th growth modls has b frthr stdid i [8]-[]. Th followig sctios ar prstd as follows: prdator-pry modls ar prstd i Sctio 2; Gomprtz modl i Sctio 3; soltio for th Prdator-pry qatios i Sctio 4; simlatio stdy i Sctio 5; aalysis of phas diagram ad qilibrim poits i Sctio 6; ad coclsios i Sctio Prdator-Pry Modls Th classical Lota-Voltrra prdator-pry modl is giv by: dx = ax bxy; dt () dy = cy + dxy. dt whr a, b, c ad d ar positiv costats. Th paramtr a is itrisic growth rat of th pry, b is rat of cosmptio of pry by prdator, c is mortality rat of prdator at absc of pry ad d is rprodctio rat of prdator d to cosmptio of pry. I th prst wor, w cosidr th cas wh th itractio of th pry ad prdator poplatios lads to a littl or o ffct o growth of th pry poplatio, that is b. W also assm th paramtr a is a fctio of tim. Ths th assmptios of th classical prdator-pry modl ar rlaxd. Th proposd prdator-pry modl is [6]: dx = r( t) x; dt (2) dy = vy + sxy. dt whr x is poplatio siz or dsity of pry; y is poplatio siz or dsity of prdator commitis i th systm. Hr w assm r to b a rlativ growth rat fctio which is positiv vald fctio of tim t. Th paramtr ss is rprodctio rat of prdator d to cosmptio of pry ad v is mortality rat of prdator at absc of pry. Both ar positiv costats. Th pry Eqatio i (2) is th first ordr diffrtial qatio. Th soltios of this first ordr diffrtial qatio ar stdid as growth modls i [9]. This implis that a pry modl ca b slctd from th larg family of growth fctios i [8] [9]. Giv pry s modl, w ca solv th diffrtial qatio of th rspctiv prdator poplatio i (2). Th gral approach for solvig Eqatio (2) cosists of th followig stps: ) ssm that th impact of prdator o pry poplatio growth is gligibl, 2) Prdator poplatio dclis i absc of pry, 3) Prdator poplatio grows with a rat proportioal to a fctio of both x ad y, 4) ssm that thr is prior iformatio abot th pry poplatio that x follows a ow growth fctio. Gomprtz growth modl i this cas. 5) Solv for prdator poplatio growth y. 3. Gomprtz Modl for Pry Poplatio Growth W assm that th growth of pry poplatio follows Gomprtz growth modl ad costrct th corrspodig 7

3 . T. Gosh, P. R. Koya prdator growth fctio. Th Gomprtz modl is giv i [9]-[2] as follows: whr B= log, x xp B t xt = (3) = is iitial poplatio siz, is asymptotic growth of th poplatio rprstig carryig capacity, ad is absolt growth rat paramtr of th pry. Th rspctiv rlativ growth rat is rt = log{ xt }. Th growth crv has a sigl poit of iflctio at tim a= ( ) log{ log ( )}. Dtaild discssio is fod i [8]-[2]. 4. Soltio of th Prdator-Pry Eqatios Hr, w solv th ordiary diffrtial qatios i (2), th dtrmi itrsctio poits at which th pry ad prdator poplatio attai sam vals, ad fially thr spcial cass of prdator poplatio ar cosidrd. 4.. Drivatio of th Modl Th soltio for th ordiary diffrtial qatio i (2) is drivd assmig that pry follows th Gomprtz modl i (3). ftr sbstittig (3) i (2), th corrspodig prdator poplatio growth fctio is drivd to b: Or qivaltly, whr y y x log log s ( v s) t =! y = y (4) y t x log = y log x log log v s s =! = rprsts iitial prdator poplatio siz. Th dtaild drivatios ar giv i ppdix. Eqatio (4) is also qivalt to th followig soltio (6) that ca b xprssd i trms of th wll ow xpotial itgral fctio Ei: y t s x vt Ei log Ei log = y (6) Not that th xpotial itgral fctio is a poplar fctio that is oft sfl i may applicatios. W bliv that this rspctiv prdator poplatio growth fctio y( t ) ca b sfl as wll. I fact, Eqatio (6) ca b xprssd algbraically as th Ei fctio: log Ei log Ei log s y s y x v = + t Th prdator modls i Eqatios (4-7) appar to b w fctios ad thy do ot match with ay o of th commoly ow growth modls Poits of Itrsctio Poits of itrsctio ar th poit of tim at which th pry ad prdator poplatios attai th sam sizs. Whvr it occrs, lt th poit of itrsctio b rprstd by p xt = yt i t, i.. w mst hav ( p) ( p) Eqatios (3) ad (4). I tryig to solv ths qatios, w gt th followig xprssio xprssd xplicitly as: t log N( t) t = sv log ( ) ( y ) (5) (7) 72

4 . T. Gosh, P. R. Koya whr N t Eqatio (7) ca oly b comptd mrically Spcial Cass log ( ) = =! To frthr drstad th modl i Eqatio (4), thr spcial cass ar idtifid which ar dpdt of birth ad dath paramtrs of prdator poplatio. Th cass ar cosidrd hr blow. Cas I ( s = v) : I this cas th fctio dscribig th poplatio growth of prdator i Eqatio (4) tas x log log s th form y( t) = y xp =!. It is frthr obsrvd that th prdator poplatio covrgs to lowr or ppr asymptot dpdig o th iitial val of th prdator poplatio. Th iitial poplatio siz ca b largr or smallr tha. Ths, th limitig val for th prdator poplatio is xp s log y y! = =. It is itrstig to ot that both th pry ad prdator poplatio sizs covrg to th sam asymptot providd that th paramtr s is assigd th val s = s log ( y) whr s =. lso th = log ( )! prdator poplatio siz covrgs to a asymptot abov or blow that of prdator poplatio siz dpdig o s = s or s = s rspctivly. Cas II ( v > s) : I this cas, th prdator poplatio dcays from y to zro as t whil th pry poplatio grows from to. Cas III ( v < s) : I this cas th prdator poplatio grows from y ad ltimatly divrgs to + as t whil th pry poplatio grows from to as xpctd or rstrictd. Th miimal poit at which th prdator growth crv trs or gts miimm val is fod to b: log ( ) tmi = ( ) log. Th th vals of pry ad prdator poplatios ar xt ( mi ) = vs ad log ( s v) s v v log log log ( ) s s y( tmi ) = y xp = log ( s v)!, rspctivly. This rslt is diffrt, for xampl, for th cas of logistic pry modl [7] for which th miimm poit occrs at s v v s tmi = log ad y( tmi ) = y s s s v v. v 73

5 . T. Gosh, P. R. Koya vs of prdator growth is propor- = whr c is a costat that ca b rlatd to a itrvtio factor applid o pry optimal siz, or a factor that ca b applid ithr to th prdator s birth parav cs vc s=. Sch itrvtio ca hc b ap- Th cass ca b gralizd to a statmt that ratio of daths to births tioal to asymptot ( ) of pry growth. That is, v s c mtr { = }, or o th prdator s dath paramtr { } plid to th pry or prdator paramtrs. Th drivatios providd i this papr corrspod to th cas that c =. For c diffrt from, th rspctiv drivatios ca similar b mad. 5. Simlatio Stdy Th simlatio stdy is carrid ot basd o Eqatio (4). Th stdy is dsigd by varyig th modl paramtrs:,, for pry poplatio followig Gomprtz modl ad y,, s v for prdator poplatio. Th stdy dsig is as follows: Pry modl: Gomprtz growth modl Pry modl paramtrs: =, = 2, =.. Prdator modl paramtrs: y =.5 is iitial poplatio siz; birth rat s, dath rat v. Cass: Cas I: s = v, Cas II: s < v, Cas III: s > v Cas I: s = & v = 8 ; s =. & v =. ; s =.356 & v =.356 ; s =. & v =.; s =.2 & v =.2 Cas II: s =. & v =.6 ; s =. & v =.2 ; s =. & v =.5 ; s =.2 & v =.25 Cas III: s =. & v =.5 ; s =. & v =.65 ; s =. & v =.95 ; s =.2 & v =.95 Th rslts of th stdy ar displayd i Figrs -3. Figr displays plots for th Cas I, whr th ratio of dath to birth of prdator is qal to asymptotic siz of pry. I th simlatio, th birth rat is varid from smallr to largr vals. Th rslt rvals that th prdator poplatio siz dcrass ad vtally covrgs to a positiv qatity at varios rats. Not that for a particlar val of th birth paramtr ss, th poplatio sizs of both pry ad prdator covrg to sam asymptotic val dotd by. Growth Cas I pry prd: s=-,v=-8 prd: s=.,v=. prd: s=.356,v=.356 prd: s=.,v=. prd: s=.2,v= Tim Figr. Plots of prdator poplatio dyamics wh pry follows Gomprtz growth modl for Cas I with =., =, = 2, y =.5. 74

6 . T. Gosh, P. R. Koya Growth Cas II pry prd: s=.,v=.6 prd: s=.,v=.2 prd: s=.,v=.5 prd: s=.2,v= Tim Figr 2. Plots of prdator poplatio dyamics wh pry follows Gomprtz growth modl for Cas II with =., =, = 2, y =.5. Growth Cas III pry prd: s=.,v=.5 prd: s=.,v=.65 prd: s=.,v=.95 prd: s=.2,v= Figr 3. Plots of prdator poplatio dyamics wh pry follows Gomprtz growth modl for Cas III with =., =, = 2, y =.5. Figr 2 displays plots for th Cas II, whr th ratio of dath to birth of prdator is largr tha. For th simlatio, w varid th rats with small magitds. Th rslt shows that th prdator poplatio dcrass ovr tim ad vtally covrgs to zro. Figr 3 displays simlatios for Cas III, whr th ratio dath/birth of prdator is lss tha. Plots ar mad for varios vals of th rats. Th rslt shows that th prdator poplatio dclis for som tim ad Tim 75

7 . T. Gosh, P. R. Koya th icrass ad vtally divrgs to ifiity. W hav show by simlatio stdy that th prdator poplatio ithr covrgs to a fiit limit or covrgs to zro or divrgs to ifiity o th positiv sid dpdig o th paramtr vals dr th assmptio that pry follows Gomprtz growth modl. Morovr, for a particlar val of birth paramtr ss, th poplatio sizs of both pry ad prdator covrg to sam asymptot. Ths fidigs ar similar with thos i [7] [8]. 6. alysis of Phas Diagram ad Eqilibrim Poits Th wly proposd prdator-pry modl (2) i its fll form ca b xprssd, i cas of Gomprtz growth of dx dt = xlog x ad dy dt = vy + sxy. Th two qilibrim pry poplatio, as th systm of qatios poits of this systm ar fod to b ( x, y ) = (,) ad ( x, y ) (,) 2 2 = sic at both ths poits th cssary ad sfficit coditios dx dt = ad dy dt = ar satisfid. lso th Jacobia matrix of th systm of qatios is J( xy, ) ( ( x) ) log =. W ow aalyz th atr of th qilibrim poits sy v + sx blow ad display th smmary i Tabl. x, y =, Natr of th Eqilibrim Poit Th Jacoba matrix at this qilibrim poit tas th form J( x, y ) J(,) ad th corrspodig igvals ar ( log ( ) ) ( ( ) ) log = = v = ad 2 = v. Rcall that all th paramtrs,, ad v ar positiv qatitis ad ths hr aris th followig two cass for whil 2 is always gativ. Coditio I log ( ) < : I this cas, both th igvals ad 2 ar gativ ad hc th { } qilibrim poit ( x, y ) = (,) is stabl. Coditio II { log ( ) } hc th qilibrim poit ( x, y ) (,) > : I this cas, th igvals is positiv whil 2 = is stabl. Natr of th Eqilibrim Poit ( x, y ) = (,) 2 2 Tabl. Smmary of stabilitis of th qilibrim poits. is gativ ad Eqilibrim poit Eigval Coditio Sig of igval Natr of qilibrim poit ( x, y ) = (,) λ log = = v 2 log < log > Both ad 2 ar gativ 2 is positiv ad is gativ Stabl Ustabl s = v 2 is gativ ad is zro Stabl ( x, y 2 2) = (,) = 2 = v + s s < v Both 2 ad ar gativ Stabl s > v 2 is gativ ad is positiv Ustabl 76

8 . T. Gosh, P. R. Koya 2 2 Th Jacoba matrix at this qilibrim poit tas th form J( x, y ) J(,) = = v + s ad th corrspodig igvals ar 2 = ad = v + s. Th paramtrs, v, s ad ar positiv ad ths implis that 2 is always gativ bt thr cass for. Coditio I { s v} is stabl. Coditio II { s v} (, x2 y2) (, ) = is stabl. Coditio III { s v} stabl. 7. Coclsios = : I this cas, v s λ = + is zro ad hc th qilibrim poit ( x, y ) = (,) < : I this cas, both th igvals ar gativ ad hc th qilibrim poit > : I this cas, oly 2 2 λ is positiv. Hc th qilibrim poit ( x, y ) (,) 2 2 = is Som mathmatical aspct of th wll ow prdator-pry problm is stdid by modifyig th rspctiv classical assmptios. W assm that th pry poplatio growths atrally with o itractio ffct d to prdatio ad rat of growth is o-costat. Th, th prdator-pry qatios ar solvd cosidrig pry grows as Gomprtz modl. Th soltio for th prdator poplatio is fod to ivolv th xpotial itgral fctio ad is qivaltly xprssd i trms of Taylor s sris. Th simlatio stdis ad frthr aalysis of th modls rval that th prdator poplatio grows i sch a way that ithr covrgs to a fiit limit or zro or divrgs to positiv ifiity. Thr is a sitatio at which both pry ad prdator poplatios covrg to th sam limit irrspctiv of thir iitial poplatio sizs. Thr is also a sitatio whr th prdator poplatio attais a miimal poit bfor it divrgs to ifiity. Morovr, two qilibrim poits ar idtifid which ar stabl oly dr som spcific coditios. Rfrcs [] Bars, B. ad Flford, G.R. (29) Mathmatical Modllig with Cas Stdis: Diffrtial Eqatios pproach sig Mapl ad MTLB. 2d Editio, Chapma ad Hall/CRC, Lodo. [2] Loga, J.D. (987) pplid Mathmatics Cotmporary pproach. J. Wily ad Sos, Hobo. [3] Chas, J.M., brams, P.., Grovr, J.P., Dihl, S., Chsso, P., Holt, R.D., Richards, S.., Nisbt, R.M. ad Cas, T.J. () Th Itractio btw Prdatio ad Comptitio: Rviw ad Sythsis. Ecology Lttrs, 5, [4] Chambrlai, S.., Brosti, J.L. ad Rdgrs, J.. (24) How Cotxt Dpdt ar Spcis Itractios? Ecology Lttrs, 7, [5] Brlow, E.L. (999) Strog Effcts of Wa Itractios i Ecological Commitis. Natr, 398, [6] Grvitch, J.J., Morriso,. ad Hdgs, L.V. (2) Th Itractio btw Comptitio ad Prdatio: Mta- alysis of Fild Exprimts. Th mrica Natralist, 55, [7] Dawd, M.Y., Koya, P.R. ad Gosh,.T. (24) Mathmatical Modllig of Poplatio Growth: Th Cas of Logistic ad Vo Brtalaffy Modls. Op Joral of Modllig ad Simlatio, 2, [8] Koya, P.R., Gosh,.T. ad Dawd, M.Y. (24) Modllig Prdator Poplatio ssmig That th Pry Follows Richards Growth Modl. Eropa Joral of cadmic Essays,, [9] Koya, P.R. ad Gosh,.T. (23) Gralizd Mathmatical Modl for Biological Growths. Op Joral of Modllig ad Simlatio,, [] Koya, P.R. ad Gosh,.T. (23) Soltios of Rat-Stat Eqatio Dscribig Biological Growths. mrica Joral of Mathmatics ad Statistics, 3, [] Gosh,.T. ad Koya, P.R. (23) Drivatio of Iflctio Poits of Noliar Rgrssio Crvs Implicatios to Statistics. mrica Joral of Thortical ad pplid Statistics, 2, [2] Wisor, C.P. (932) Th Gomprtz Crv as a Growth Crv. Procdigs of th Natioal cadmy of Scics of th Uitd Stats of mrica, 8,

9 . T. Gosh, P. R. Koya ppdix Drivatio of Prdator Poplatio Modl giv Pry follows Gomprtz Growth Modl ssm th pry poplatio growth ca b rprstd by th Gomprtz fctio: Th th prdator qatio ca b solvd as: Sbstittig (i) i (ii) givs B xt =, B= log dy dy = vy + sxy = [ v + sx] dt logy = vt s xdt dt y + (ii) B log d y = vt + s t W ow itrodc a w variabl for th prpos of valatig th itgral as So as to gt: = B d = dt dt = d To valat th itgral, w ow s Taylor s sris xpasio of Hc Usig (iv) i (iii), w gt: = or =! s logy = vt d (iii) 2 = ! 3! d = log + =! as: (iv) s logy = vt log + C = + (v)! To dtrmi th itgral costat C w ow impos th iitial coditios ad y. That rdcs (v) to b: To limiat C, sbtract (vi) from (v) to gt: t B Bt log = log = B Ths, (vi) ca b rarragd as: s logy = log + C = +! (vi) y s t t log = vt log + = y (vi)! x log =. t with ( t) = B = log, x log log s ( v s) t =! y t = y (vii) (i) 78

10 . T. Gosh, P. R. Koya Ths y( t ) is prdator poplatio siz at t. Usig y t ( x) ( ) log = y log ( x) ( ) log = log ( v s) x log log s =! i (vii), w hav Th rlatioship (viii) is a phas path qatio. It ca b sd to aalyz phas path diagrams. (viii) ppdix 2 Show th Soltio with Expotial Itgral Fctio ad th Taylor s Sris of th Prdator Poplatio ar Eqivalt. Expotial itgral fctio Ei( x ), for small vals of x, is giv by Maclari sris as: Ei x = + + (i) =! ( x) γ logx Hr γ =.5772 is calld Elr s costat. Usig (i), th xprssios for Ei log x ad Ei log ca b obtaid as follows: O sbtractig (iii) from (ii), w gt Bt th xprssio x log x x Ei log γ log log = + + = (ii)! log x (iii)! Ei log = γ + log log + = x x log log log x = + (iv)! log Ei log Ei log log = x log log log Hc, sig (v) i (iv) w gt ca b simplifid sig (2) as x log B log = log = log ( ) = B log x log log x Ei log Ei log t = + = (vi)! (v) 79

11 . T. Gosh, P. R. Koya Usig (v) i (i), w gt Or qivaltly y = y x log log s vt t + =! x log log s ( v s) t =! y = y (vii) Ths (vii) is th rqird prdator qatio xprssd sig xpotial itgral fctio Ei( x ). Sic (vii) is drivd from (i), it ca b drstood that both th soltios obtaid sig Taylor s sris xpasio ad Expotial itgral fctio agr with ach othr. Not that th idfiit itgral d togthr with th iitial coditio L th smi-dfiit itgral as a w dw. Th lowr limit is fixd. w = a ca b xprssd as 8

10. Joint Moments and Joint Characteristic Functions

10. Joint Moments and Joint Characteristic Functions 0 Joit Momts ad Joit Charactristic Fctios Followig sctio 6 i this sctio w shall itrodc varios paramtrs to compactly rprst th iformatio cotaid i th joit pdf of two rvs Giv two rvs ad ad a fctio g x y dfi

More information

1985 AP Calculus BC: Section I

1985 AP Calculus BC: Section I 985 AP Calculus BC: Sctio I 9 Miuts No Calculator Nots: () I this amiatio, l dots th atural logarithm of (that is, logarithm to th bas ). () Ulss othrwis spcifid, th domai of a fuctio f is assumd to b

More information

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series

Chapter 2 Infinite Series Page 1 of 11. Chapter 2 : Infinite Series Chatr Ifiit Sris Pag of Sctio F Itgral Tst Chatr : Ifiit Sris By th d of this sctio you will b abl to valuat imror itgrals tst a sris for covrgc by alyig th itgral tst aly th itgral tst to rov th -sris

More information

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z

z 1+ 3 z = Π n =1 z f() z = n e - z = ( 1-z) e z e n z z 1- n = ( 1-z/2) 1+ 2n z e 2n e n -1 ( 1-z )/2 e 2n-1 1-2n -1 1 () z Sris Expasio of Rciprocal of Gamma Fuctio. Fuctios with Itgrs as Roots Fuctio f with gativ itgrs as roots ca b dscribd as follows. f() Howvr, this ifiit product divrgs. That is, such a fuctio caot xist

More information

Fooling Newton s Method a) Find a formula for the Newton sequence, and verify that it converges to a nonzero of f. A Stirling-like Inequality

Fooling Newton s Method a) Find a formula for the Newton sequence, and verify that it converges to a nonzero of f. A Stirling-like Inequality Foolig Nwto s Mthod a Fid a formla for th Nwto sqc, ad vrify that it covrgs to a ozro of f. ( si si + cos 4 4 3 4 8 8 bt f. b Fid a formla for f ( ad dtrmi its bhavior as. f ( cos si + as A Stirlig-li

More information

PURE MATHEMATICS A-LEVEL PAPER 1

PURE MATHEMATICS A-LEVEL PAPER 1 -AL P MATH PAPER HONG KONG EXAMINATIONS AUTHORITY HONG KONG ADVANCED LEVEL EXAMINATION PURE MATHEMATICS A-LEVEL PAPER 8 am am ( hours) This papr must b aswrd i Eglish This papr cosists of Sctio A ad Sctio

More information

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges.

Option 3. b) xe dx = and therefore the series is convergent. 12 a) Divergent b) Convergent Proof 15 For. p = 1 1so the series diverges. Optio Chaptr Ercis. Covrgs to Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Divrgs 8 Divrgs Covrgs to Covrgs to Divrgs Covrgs to Covrgs to Covrgs to Covrgs to 8 Proof Covrgs to π l 8 l a b Divrgt π Divrgt

More information

Statistics 3858 : Likelihood Ratio for Exponential Distribution

Statistics 3858 : Likelihood Ratio for Exponential Distribution Statistics 3858 : Liklihood Ratio for Expotial Distributio I ths two xampl th rjctio rjctio rgio is of th form {x : 2 log (Λ(x)) > c} for a appropriat costat c. For a siz α tst, usig Thorm 9.5A w obtai

More information

They must have different numbers of electrons orbiting their nuclei. They must have the same number of neutrons in their nuclei.

They must have different numbers of electrons orbiting their nuclei. They must have the same number of neutrons in their nuclei. 37 1 How may utros ar i a uclus of th uclid l? 20 37 54 2 crtai lmt has svral isotops. Which statmt about ths isotops is corrct? Thy must hav diffrt umbrs of lctros orbitig thir ucli. Thy must hav th sam

More information

15/03/1439. Lectures on Signals & systems Engineering

15/03/1439. Lectures on Signals & systems Engineering Lcturs o Sigals & syms Egirig Dsigd ad Prd by Dr. Ayma Elshawy Elsfy Dpt. of Syms & Computr Eg. Al-Azhar Uivrsity Email : aymalshawy@yahoo.com A sigal ca b rprd as a liar combiatio of basic sigals. Th

More information

Washington State University

Washington State University he 3 Ktics ad Ractor Dsig Sprg, 00 Washgto Stat Uivrsity Dpartmt of hmical Egrg Richard L. Zollars Exam # You will hav o hour (60 muts) to complt this xam which cosists of four (4) problms. You may us

More information

H2 Mathematics Arithmetic & Geometric Series ( )

H2 Mathematics Arithmetic & Geometric Series ( ) H Mathmatics Arithmtic & Gomtric Sris (08 09) Basic Mastry Qustios Arithmtic Progrssio ad Sris. Th rth trm of a squc is 4r 7. (i) Stat th first four trms ad th 0th trm. (ii) Show that th squc is a arithmtic

More information

APPENDIX: STATISTICAL TOOLS

APPENDIX: STATISTICAL TOOLS I. Nots o radom samplig Why do you d to sampl radomly? APPENDI: STATISTICAL TOOLS I ordr to masur som valu o a populatio of orgaisms, you usually caot masur all orgaisms, so you sampl a subst of th populatio.

More information

On the approximation of the constant of Napier

On the approximation of the constant of Napier Stud. Uiv. Babş-Bolyai Math. 560, No., 609 64 O th approximatio of th costat of Napir Adri Vrscu Abstract. Startig from som oldr idas of [] ad [6], w show w facts cocrig th approximatio of th costat of

More information

A Simple Proof that e is Irrational

A Simple Proof that e is Irrational Two of th most bautiful ad sigificat umbrs i mathmatics ar π ad. π (approximatly qual to 3.459) rprsts th ratio of th circumfrc of a circl to its diamtr. (approximatly qual to.788) is th bas of th atural

More information

Review Exercises. 1. Evaluate using the definition of the definite integral as a Riemann Sum. Does the answer represent an area? 2

Review Exercises. 1. Evaluate using the definition of the definite integral as a Riemann Sum. Does the answer represent an area? 2 MATHEMATIS --RE Itgral alculus Marti Huard Witr 9 Rviw Erciss. Evaluat usig th dfiitio of th dfiit itgral as a Rima Sum. Dos th aswr rprst a ara? a ( d b ( d c ( ( d d ( d. Fid f ( usig th Fudamtal Thorm

More information

A Prey-Predator Model with an Alternative Food for the Predator, Harvesting of Both the Species and with A Gestation Period for Interaction

A Prey-Predator Model with an Alternative Food for the Predator, Harvesting of Both the Species and with A Gestation Period for Interaction Int. J. Opn Problms Compt. Math., Vol., o., Jun 008 A Pry-Prdator Modl with an Altrnativ Food for th Prdator, Harvsting of Both th Spcis and with A Gstation Priod for Intraction K. L. arayan and. CH. P.

More information

MONTGOMERY COLLEGE Department of Mathematics Rockville Campus. 6x dx a. b. cos 2x dx ( ) 7. arctan x dx e. cos 2x dx. 2 cos3x dx

MONTGOMERY COLLEGE Department of Mathematics Rockville Campus. 6x dx a. b. cos 2x dx ( ) 7. arctan x dx e. cos 2x dx. 2 cos3x dx MONTGOMERY COLLEGE Dpartmt of Mathmatics Rockvill Campus MATH 8 - REVIEW PROBLEMS. Stat whthr ach of th followig ca b itgratd by partial fractios (PF), itgratio by parts (PI), u-substitutio (U), or o of

More information

Lectures 9 IIR Systems: First Order System

Lectures 9 IIR Systems: First Order System EE3054 Sigals ad Systms Lcturs 9 IIR Systms: First Ordr Systm Yao Wag Polytchic Uivrsity Som slids icludd ar xtractd from lctur prstatios prpard by McCllla ad Schafr Lics Ifo for SPFirst Slids This work

More information

Probability & Statistics,

Probability & Statistics, Probability & Statistics, BITS Pilai K K Birla Goa Campus Dr. Jajati Kshari Sahoo Dpartmt of Mathmatics BITS Pilai, K K Birla Goa Campus Poisso Distributio Poisso Distributio: A radom variabl X is said

More information

The Interplay between l-max, l-min, p-max and p-min Stable Distributions

The Interplay between l-max, l-min, p-max and p-min Stable Distributions DOI: 0.545/mjis.05.4006 Th Itrplay btw lma lmi pma ad pmi Stabl Distributios S Ravi ad TS Mavitha Dpartmt of Studis i Statistics Uivrsity of Mysor Maasagagotri Mysuru 570006 Idia. Email:ravi@statistics.uimysor.ac.i

More information

NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES

NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES Digst Joural of Naomatrials ad Biostructurs Vol 4, No, March 009, p 67-76 NEW VERSION OF SZEGED INDEX AND ITS COMPUTATION FOR SOME NANOTUBES A IRANMANESH a*, O KHORMALI b, I NAJAFI KHALILSARAEE c, B SOLEIMANI

More information

Digital Signal Processing, Fall 2006

Digital Signal Processing, Fall 2006 Digital Sigal Procssig, Fall 6 Lctur 9: Th Discrt Fourir Trasfor Zhg-Hua Ta Dpartt of Elctroic Systs Aalborg Uivrsity, Dar zt@o.aau.d Digital Sigal Procssig, I, Zhg-Hua Ta, 6 Cours at a glac MM Discrt-ti

More information

Solution to 1223 The Evil Warden.

Solution to 1223 The Evil Warden. Solutio to 1 Th Evil Ward. This is o of thos vry rar PoWs (I caot thik of aothr cas) that o o solvd. About 10 of you submittd th basic approach, which givs a probability of 47%. I was shockd wh I foud

More information

Chapter 3 Fourier Series Representation of Periodic Signals

Chapter 3 Fourier Series Representation of Periodic Signals Chptr Fourir Sris Rprsttio of Priodic Sigls If ritrry sigl x(t or x[] is xprssd s lir comitio of som sic sigls th rspos of LI systm coms th sum of th idividul rsposs of thos sic sigls Such sic sigl must:

More information

Discrete Fourier Transform (DFT)

Discrete Fourier Transform (DFT) Discrt Fourir Trasorm DFT Major: All Egirig Majors Authors: Duc guy http://umricalmthods.g.us.du umrical Mthods or STEM udrgraduats 8/3/29 http://umricalmthods.g.us.du Discrt Fourir Trasorm Rcalld th xpotial

More information

Journal of Modern Applied Statistical Methods

Journal of Modern Applied Statistical Methods Joural of Modr Applid Statistical Mthods Volum Issu Articl 6 --03 O Som Proprtis of a Htrogous Trasfr Fuctio Ivolvig Symmtric Saturatd Liar (SATLINS) with Hyprbolic Tagt (TANH) Trasfr Fuctios Christophr

More information

On a problem of J. de Graaf connected with algebras of unbounded operators de Bruijn, N.G.

On a problem of J. de Graaf connected with algebras of unbounded operators de Bruijn, N.G. O a problm of J. d Graaf coctd with algbras of uboudd oprators d Bruij, N.G. Publishd: 01/01/1984 Documt Vrsio Publishr s PDF, also kow as Vrsio of Rcord (icluds fial pag, issu ad volum umbrs) Plas chck

More information

5.1 The Nuclear Atom

5.1 The Nuclear Atom Sav My Exams! Th Hom of Rvisio For mor awsom GSE ad lvl rsourcs, visit us at www.savmyxams.co.uk/ 5.1 Th Nuclar tom Qustio Papr Lvl IGSE Subjct Physics (0625) Exam oard Topic Sub Topic ooklt ambridg Itratioal

More information

Where k is either given or determined from the data and c is an arbitrary constant.

Where k is either given or determined from the data and c is an arbitrary constant. Exponntial growth and dcay applications W wish to solv an quation that has a drivativ. dy ky k > dx This quation says that th rat of chang of th function is proportional to th function. Th solution is

More information

Hadamard Exponential Hankel Matrix, Its Eigenvalues and Some Norms

Hadamard Exponential Hankel Matrix, Its Eigenvalues and Some Norms Math Sci Ltt Vol No 8-87 (0) adamard Exotial al Matrix, Its Eigvalus ad Som Norms İ ad M bula Mathmatical Scics Lttrs Itratioal Joural @ 0 NSP Natural Scics Publishig Cor Dartmt of Mathmatics, aculty of

More information

An Introduction to Asymptotic Expansions

An Introduction to Asymptotic Expansions A Itroductio to Asmptotic Expasios R. Shaar Subramaia Asmptotic xpasios ar usd i aalsis to dscrib th bhavior of a fuctio i a limitig situatio. Wh a fuctio ( x, dpds o a small paramtr, ad th solutio of

More information

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net

Worksheet: Taylor Series, Lagrange Error Bound ilearnmath.net Taylor s Thorm & Lagrag Error Bouds Actual Error This is th ral amout o rror, ot th rror boud (worst cas scario). It is th dirc btw th actual () ad th polyomial. Stps:. Plug -valu ito () to gt a valu.

More information

Chapter Taylor Theorem Revisited

Chapter Taylor Theorem Revisited Captr 0.07 Taylor Torm Rvisitd Atr radig tis captr, you sould b abl to. udrstad t basics o Taylor s torm,. writ trascdtal ad trigoomtric uctios as Taylor s polyomial,. us Taylor s torm to id t valus o

More information

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES

LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES LECTURE 6 TRANSFORMATION OF RANDOM VARIABLES TRANSFORMATION OF FUNCTION OF A RANDOM VARIABLE UNIVARIATE TRANSFORMATIONS TRANSFORMATION OF RANDOM VARIABLES If s a rv wth cdf F th Y=g s also a rv. If w wrt

More information

Reliability of time dependent stress-strength system for various distributions

Reliability of time dependent stress-strength system for various distributions IOS Joural of Mathmatcs (IOS-JM ISSN: 78-578. Volum 3, Issu 6 (Sp-Oct., PP -7 www.osrjourals.org lablty of tm dpdt strss-strgth systm for varous dstrbutos N.Swath, T.S.Uma Mahswar,, Dpartmt of Mathmatcs,

More information

Chapter 11.00C Physical Problem for Fast Fourier Transform Civil Engineering

Chapter 11.00C Physical Problem for Fast Fourier Transform Civil Engineering haptr. Physical Problm for Fast Fourir Trasform ivil Egirig Itroductio I this chaptr, applicatios of FFT algorithms [-5] for solvig ral-lif problms such as computig th dyamical (displacmt rspos [6-7] of

More information

Class #24 Monday, April 16, φ φ φ

Class #24 Monday, April 16, φ φ φ lass #4 Moday, April 6, 08 haptr 3: Partial Diffrtial Equatios (PDE s First of all, this sctio is vry, vry difficult. But it s also supr cool. PDE s thr is mor tha o idpdt variabl. Exampl: φ φ φ φ = 0

More information

Time : 1 hr. Test Paper 08 Date 04/01/15 Batch - R Marks : 120

Time : 1 hr. Test Paper 08 Date 04/01/15 Batch - R Marks : 120 Tim : hr. Tst Papr 8 D 4//5 Bch - R Marks : SINGLE CORRECT CHOICE TYPE [4, ]. If th compl umbr z sisfis th coditio z 3, th th last valu of z is qual to : z (A) 5/3 (B) 8/3 (C) /3 (D) o of ths 5 4. Th itgral,

More information

Bipolar Junction Transistors

Bipolar Junction Transistors ipolar Juctio Trasistors ipolar juctio trasistors (JT) ar activ 3-trmial dvics with aras of applicatios: amplifirs, switch tc. high-powr circuits high-spd logic circuits for high-spd computrs. JT structur:

More information

Narayana IIT Academy

Narayana IIT Academy INDIA Sc: LT-IIT-SPARK Dat: 9--8 6_P Max.Mars: 86 KEY SHEET PHYSIS A 5 D 6 7 A,B 8 B,D 9 A,B A,,D A,B, A,B B, A,B 5 A 6 D 7 8 A HEMISTRY 9 A B D B B 5 A,B,,D 6 A,,D 7 B,,D 8 A,B,,D 9 A,B, A,B, A,B,,D A,B,

More information

International Journal of Advanced and Applied Sciences

International Journal of Advanced and Applied Sciences Itratioal Joural of Advacd ad Applid Scics x(x) xxxx Pags: xx xx Cotts lists availabl at Scic Gat Itratioal Joural of Advacd ad Applid Scics Joural hompag: http://wwwscic gatcom/ijaashtml Symmtric Fuctios

More information

How many neutrino species?

How many neutrino species? ow may utrio scis? Two mthods for dtrmii it lium abudac i uivrs At a collidr umbr of utrio scis Exasio of th uivrs is ovrd by th Fridma quatio R R 8G tot Kc R Whr: :ubblcostat G :Gravitatioal costat 6.

More information

2008 AP Calculus BC Multiple Choice Exam

2008 AP Calculus BC Multiple Choice Exam 008 AP Multipl Choic Eam Nam 008 AP Calculus BC Multipl Choic Eam Sction No Calculator Activ AP Calculus 008 BC Multipl Choic. At tim t 0, a particl moving in th -plan is th acclration vctor of th particl

More information

Restricted Factorial And A Remark On The Reduced Residue Classes

Restricted Factorial And A Remark On The Reduced Residue Classes Applid Mathmatics E-Nots, 162016, 244-250 c ISSN 1607-2510 Availabl fr at mirror sits of http://www.math.thu.du.tw/ am/ Rstrictd Factorial Ad A Rmark O Th Rducd Rsidu Classs Mhdi Hassai Rcivd 26 March

More information

Frequency Measurement in Noise

Frequency Measurement in Noise Frqucy Masurmt i ois Porat Sctio 6.5 /4 Frqucy Mas. i ois Problm Wat to o look at th ct o ois o usig th DFT to masur th rqucy o a siusoid. Cosidr sigl complx siusoid cas: j y +, ssum Complx Whit ois Gaussia,

More information

Mixed Mode Oscillations as a Mechanism for Pseudo-Plateau Bursting

Mixed Mode Oscillations as a Mechanism for Pseudo-Plateau Bursting Mixd Mod Oscillatios as a Mchaism for Psudo-Platau Burstig Richard Brtram Dpartmt of Mathmatics Florida Stat Uivrsity Tallahass, FL Collaborators ad Support Thodor Vo Marti Wchslbrgr Joël Tabak Uivrsity

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by Dan Klain Vrsion 28928 Corrctions and commnts ar wlcom Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix () A A k I + A + k!

More information

The Variational Iteration Method for Analytic Treatment of Homogeneous and Inhomogeneous Partial Differential Equations

The Variational Iteration Method for Analytic Treatment of Homogeneous and Inhomogeneous Partial Differential Equations Global Joral of Scic Frotir Rarch: F Mathmatic ad Dciio Scic Volm 5 I 5 Vrio Yar 5 Tp : Dobl Blid Pr Rviwd Itratioal Rarch Joral Pblihr: Global Joral Ic USA Oli ISSN: 9- & Prit ISSN: 975-589 Th Variatioal

More information

The Matrix Exponential

The Matrix Exponential Th Matrix Exponntial (with xrciss) by D. Klain Vrsion 207.0.05 Corrctions and commnts ar wlcom. Th Matrix Exponntial For ach n n complx matrix A, dfin th xponntial of A to b th matrix A A k I + A + k!

More information

Normal Form for Systems with Linear Part N 3(n)

Normal Form for Systems with Linear Part N 3(n) Applid Mathmatics 64-647 http://dxdoiorg/46/am7 Publishd Oli ovmbr (http://wwwscirporg/joural/am) ormal Form or Systms with Liar Part () Grac Gachigua * David Maloza Johaa Sigy Dpartmt o Mathmatics Collg

More information

macro Road map to this lecture Objectives Aggregate Supply and the Phillips Curve Three models of aggregate supply W = ω P The sticky-wage model

macro Road map to this lecture Objectives Aggregate Supply and the Phillips Curve Three models of aggregate supply W = ω P The sticky-wage model Road map to this lctur macro Aggrgat Supply ad th Phillips Curv W rlax th assumptio that th aggrgat supply curv is vrtical A vrsio of th aggrgat supply i trms of iflatio (rathr tha th pric lvl is calld

More information

Ch. 24 Molecular Reaction Dynamics 1. Collision Theory

Ch. 24 Molecular Reaction Dynamics 1. Collision Theory Ch. 4 Molcular Raction Dynamics 1. Collision Thory Lctur 16. Diffusion-Controlld Raction 3. Th Matrial Balanc Equation 4. Transition Stat Thory: Th Eyring Equation 5. Transition Stat Thory: Thrmodynamic

More information

CDS 101: Lecture 5.1 Reachability and State Space Feedback

CDS 101: Lecture 5.1 Reachability and State Space Feedback CDS, Lctur 5. CDS : Lctur 5. Rachability ad Stat Spac Fdback Richard M. Murray ad Hido Mabuchi 5 Octobr 4 Goals: Di rachability o a cotrol systm Giv tsts or rachability o liar systms ad apply to ampls

More information

Character sums over generalized Lehmer numbers

Character sums over generalized Lehmer numbers Ma t al. Joural of Iualitis ad Applicatios 206 206:270 DOI 0.86/s3660-06-23-y R E S E A R C H Op Accss Charactr sums ovr gralizd Lhmr umbrs Yuakui Ma, Hui Ch 2, Zhzh Qi 2 ad Tiapig Zhag 2* * Corrspodc:

More information

ln x = n e = 20 (nearest integer)

ln x = n e = 20 (nearest integer) H JC Prlim Solutios 6 a + b y a + b / / dy a b 3/ d dy a b at, d Giv quatio of ormal at is y dy ad y wh. d a b () (,) is o th curv a+ b () y.9958 Qustio Solvig () ad (), w hav a, b. Qustio d.77 d d d.77

More information

CDS 101: Lecture 5.1 Reachability and State Space Feedback

CDS 101: Lecture 5.1 Reachability and State Space Feedback CDS, Lctur 5. CDS : Lctur 5. Rachability ad Stat Spac Fdback Richard M. Murray 7 Octobr 3 Goals: Di rachability o a cotrol systm Giv tsts or rachability o liar systms ad apply to ampls Dscrib th dsig o

More information

DTFT Properties. Example - Determine the DTFT Y ( e ) of n. Let. We can therefore write. From Table 3.1, the DTFT of x[n] is given by 1

DTFT Properties. Example - Determine the DTFT Y ( e ) of n. Let. We can therefore write. From Table 3.1, the DTFT of x[n] is given by 1 DTFT Proprtis Exampl - Dtrmi th DTFT Y of y α µ, α < Lt x α µ, α < W ca thrfor writ y x x From Tabl 3., th DTFT of x is giv by ω X ω α ω Copyright, S. K. Mitra Copyright, S. K. Mitra DTFT Proprtis DTFT

More information

Session : Plasmas in Equilibrium

Session : Plasmas in Equilibrium Sssio : Plasmas i Equilibrium Ioizatio ad Coductio i a High-prssur Plasma A ormal gas at T < 3000 K is a good lctrical isulator, bcaus thr ar almost o fr lctros i it. For prssurs > 0.1 atm, collisio amog

More information

Triple Play: From De Morgan to Stirling To Euler to Maclaurin to Stirling

Triple Play: From De Morgan to Stirling To Euler to Maclaurin to Stirling Tripl Play: From D Morga to Stirlig To Eulr to Maclauri to Stirlig Augustus D Morga (186-1871) was a sigificat Victoria Mathmaticia who mad cotributios to Mathmatics History, Mathmatical Rcratios, Mathmatical

More information

LECTURE 13 Filling the bands. Occupancy of Available Energy Levels

LECTURE 13 Filling the bands. Occupancy of Available Energy Levels LUR 3 illig th bads Occupacy o Availabl rgy Lvls W hav dtrmid ad a dsity o stats. W also d a way o dtrmiig i a stat is illd or ot at a giv tmpratur. h distributio o th rgis o a larg umbr o particls ad

More information

An Extensive Study of Approximating the Periodic. Solutions of the Prey Predator System

An Extensive Study of Approximating the Periodic. Solutions of the Prey Predator System pplid athmatical Scincs Vol. 00 no. 5 5 - n xtnsiv Study of pproximating th Priodic Solutions of th Pry Prdator Systm D. Vnu Gopala Rao * ailing addrss: Plot No.59 Sctor-.V.P.Colony Visahapatnam 50 07

More information

Iterative Methods of Order Four for Solving Nonlinear Equations

Iterative Methods of Order Four for Solving Nonlinear Equations Itrativ Mods of Ordr Four for Solvig Noliar Equatios V.B. Kumar,Vatti, Shouri Domii ad Mouia,V Dpartmt of Egirig Mamatis, Formr Studt of Chmial Egirig Adhra Uivrsity Collg of Egirig A, Adhra Uivrsity Visakhapatam

More information

Linear Algebra Existence of the determinant. Expansion according to a row.

Linear Algebra Existence of the determinant. Expansion according to a row. Lir Algbr 2270 1 Existc of th dtrmit. Expsio ccordig to row. W dfi th dtrmit for 1 1 mtrics s dt([]) = (1) It is sy chck tht it stisfis D1)-D3). For y othr w dfi th dtrmit s follows. Assumig th dtrmit

More information

A NEW CURRENT TRANSFORMER SATURATION DETECTION ALGORITHM

A NEW CURRENT TRANSFORMER SATURATION DETECTION ALGORITHM A NEW CURRENT TRANSFORMER SATURATION DETECTION ALGORITHM CHAPTER 5 I uit protctio schms, whr CTs ar diffrtially coctd, th xcitatio charactristics of all CTs should b wll matchd. Th primary currt flow o

More information

PPS (Pottial Path Spac) i y i l j Vij (2) H x PP (Pottial Path ra) (gravity-typ masur) i i i j1 cij (1) D j j c ij ij 4)7) 8), 9) D j V ij j i 198 1)1

PPS (Pottial Path Spac) i y i l j Vij (2) H x PP (Pottial Path ra) (gravity-typ masur) i i i j1 cij (1) D j j c ij ij 4)7) 8), 9) D j V ij j i 198 1)1 1 2 3 1 (68-8552 4 11) E-mail: taimoto@ss.tottori-u.ac.jp 2 (68-8552 4 11) 3 (657-851 1-1) Ky Words: accssibility, public trasportatio plaig, rural aras, tim allocatio, spac-tim prism 197 Hady ad Nimir

More information

Learning objectives. Three models of aggregate supply. 1. The sticky-wage model 2. The imperfect-information model 3. The sticky-price model

Learning objectives. Three models of aggregate supply. 1. The sticky-wage model 2. The imperfect-information model 3. The sticky-price model Larig objctivs thr modls of aggrgat supply i which output dpds positivly o th pric lvl i th short ru th short-ru tradoff btw iflatio ad umploymt kow as th Phillips curv Aggrgat Supply slid 1 Thr modls

More information

8(4 m0) ( θ ) ( ) Solutions for HW 8. Chapter 25. Conceptual Questions

8(4 m0) ( θ ) ( ) Solutions for HW 8. Chapter 25. Conceptual Questions Solutios for HW 8 Captr 5 Cocptual Qustios 5.. θ dcrass. As t crystal is coprssd, t spacig d btw t plas of atos dcrass. For t first ordr diffractio =. T Bragg coditio is = d so as d dcrass, ust icras for

More information

ph People Grade Level: basic Duration: minutes Setting: classroom or field site

ph People Grade Level: basic Duration: minutes Setting: classroom or field site ph Popl Adaptd from: Whr Ar th Frogs? in Projct WET: Curriculum & Activity Guid. Bozman: Th Watrcours and th Council for Environmntal Education, 1995. ph Grad Lvl: basic Duration: 10 15 minuts Stting:

More information

Ordinary Differential Equations

Ordinary Differential Equations Basi Nomlatur MAE 0 all 005 Egirig Aalsis Ltur Nots o: Ordiar Diffrtial Equatios Author: Profssor Albrt Y. Tog Tpist: Sakurako Takahashi Cosidr a gral O. D. E. with t as th idpdt variabl, ad th dpdt variabl.

More information

2.29 Numerical Fluid Mechanics Spring 2015 Lecture 12

2.29 Numerical Fluid Mechanics Spring 2015 Lecture 12 REVIEW Lctur 11: Numrical Fluid Mchaics Sprig 2015 Lctur 12 Fiit Diffrcs basd Polyomial approximatios Obtai polyomial (i gral u-qually spacd), th diffrtiat as dd Nwto s itrpolatig polyomial formulas Triagular

More information

Law of large numbers

Law of large numbers Law of larg umbrs Saya Mukhrj W rvisit th law of larg umbrs ad study i som dtail two typs of law of larg umbrs ( 0 = lim S ) p ε ε > 0, Wak law of larrg umbrs [ ] S = ω : lim = p, Strog law of larg umbrs

More information

Chapter (8) Estimation and Confedence Intervals Examples

Chapter (8) Estimation and Confedence Intervals Examples Chaptr (8) Estimatio ad Cofdc Itrvals Exampls Typs of stimatio: i. Poit stimatio: Exampl (1): Cosidr th sampl obsrvatios, 17,3,5,1,18,6,16,10 8 X i i1 17 3 5 118 6 16 10 116 X 14.5 8 8 8 14.5 is a poit

More information

Estimation of apparent fraction defective: A mathematical approach

Estimation of apparent fraction defective: A mathematical approach Availabl onlin at www.plagiarsarchlibrary.com Plagia Rsarch Library Advancs in Applid Scinc Rsarch, 011, (): 84-89 ISSN: 0976-8610 CODEN (USA): AASRFC Estimation of apparnt fraction dfctiv: A mathmatical

More information

THE CONSERVATIVE DIFFERENCE SCHEME FOR THE GENERALIZED ROSENAU-KDV EQUATION

THE CONSERVATIVE DIFFERENCE SCHEME FOR THE GENERALIZED ROSENAU-KDV EQUATION Zho, J., et al.: The Coservative Differece Scheme for the Geeralized THERMAL SCIENCE, Year 6, Vol., Sppl. 3, pp. S93-S9 S93 THE CONSERVATIVE DIFFERENCE SCHEME FOR THE GENERALIZED ROSENAU-KDV EQUATION by

More information

7. Differentiation of Trigonometric Function

7. Differentiation of Trigonometric Function 7. Diffrtiatio of Trigootric Fctio RADIAN MEASURE. Lt s ot th lgth of arc AB itrcpt y th ctral agl AOB o a circl of rais r a lt S ot th ara of th sctor AOB. (If s is /60 of th circfrc, AOB = 0 ; if s =

More information

Calculus & analytic geometry

Calculus & analytic geometry Calculus & aalytic gomtry B Sc MATHEMATICS Admissio owards IV SEMESTER CORE COURSE UNIVERSITY OF CALICUT SCHOOL OF DISTANCE EDUCATION CALICUT UNIVERSITYPO, MALAPPURAM, KERALA, INDIA 67 65 5 School of Distac

More information

Einstein Equations for Tetrad Fields

Einstein Equations for Tetrad Fields Apiron, Vol 13, No, Octobr 006 6 Einstin Equations for Ttrad Filds Ali Rıza ŞAHİN, R T L Istanbul (Turky) Evry mtric tnsor can b xprssd by th innr product of ttrad filds W prov that Einstin quations for

More information

Homotopy perturbation technique

Homotopy perturbation technique Comput. Mthods Appl. Mch. Engrg. 178 (1999) 257±262 www.lsvir.com/locat/cma Homotopy prturbation tchniqu Ji-Huan H 1 Shanghai Univrsity, Shanghai Institut of Applid Mathmatics and Mchanics, Shanghai 272,

More information

NET/JRF, GATE, IIT JAM, JEST, TIFR

NET/JRF, GATE, IIT JAM, JEST, TIFR Istitut for NET/JRF, GATE, IIT JAM, JEST, TIFR ad GRE i PHYSICAL SCIENCES Mathmatical Physics JEST-6 Q. Giv th coditio φ, th solutio of th quatio ψ φ φ is giv by k. kφ kφ lφ kφ lφ (a) ψ (b) ψ kφ (c) ψ

More information

Chapter 4 - The Fourier Series

Chapter 4 - The Fourier Series M. J. Robrts - 8/8/4 Chaptr 4 - Th Fourir Sris Slctd Solutios (I this solutio maual, th symbol,, is usd for priodic covolutio bcaus th prfrrd symbol which appars i th txt is ot i th fot slctio of th word

More information

07 - SEQUENCES AND SERIES Page 1 ( Answers at he end of all questions ) b, z = n

07 - SEQUENCES AND SERIES Page 1 ( Answers at he end of all questions ) b, z = n 07 - SEQUENCES AND SERIES Pag ( Aswrs at h d of all qustios ) ( ) If = a, y = b, z = c, whr a, b, c ar i A.P. ad = 0 = 0 = 0 l a l

More information

A Note on Quantile Coupling Inequalities and Their Applications

A Note on Quantile Coupling Inequalities and Their Applications A Not o Quatil Couplig Iqualitis ad Thir Applicatios Harriso H. Zhou Dpartmt of Statistics, Yal Uivrsity, Nw Hav, CT 06520, USA. E-mail:huibi.zhou@yal.du Ju 2, 2006 Abstract A rlatioship btw th larg dviatio

More information

Derivation of a Predictor of Combination #1 and the MSE for a Predictor of a Position in Two Stage Sampling with Response Error.

Derivation of a Predictor of Combination #1 and the MSE for a Predictor of a Position in Two Stage Sampling with Response Error. Drivatio of a Prdictor of Cobiatio # ad th SE for a Prdictor of a Positio i Two Stag Saplig with Rspos Error troductio Ed Stak W driv th prdictor ad its SE of a prdictor for a rado fuctio corrspodig to

More information

Introduction - the economics of incomplete information

Introduction - the economics of incomplete information Introdction - th conomics of incomplt information Backgrond: Noclassical thory of labor spply: No nmploymnt, individals ithr mployd or nonparticipants. Altrnativs: Job sarch Workrs hav incomplt info on

More information

Global Chaos Synchronization of the Hyperchaotic Qi Systems by Sliding Mode Control

Global Chaos Synchronization of the Hyperchaotic Qi Systems by Sliding Mode Control Dr. V. Sudarapadia t al. / Itratioal Joural o Computr Scic ad Egirig (IJCSE) Global Chaos Sychroizatio of th Hyprchaotic Qi Systms by Slidig Mod Cotrol Dr. V. Sudarapadia Profssor, Rsarch ad Dvlopmt Ctr

More information

STIRLING'S 1 FORMULA AND ITS APPLICATION

STIRLING'S 1 FORMULA AND ITS APPLICATION MAT-KOL (Baja Luka) XXIV ()(08) 57-64 http://wwwimviblorg/dmbl/dmblhtm DOI: 075/МК80057A ISSN 0354-6969 (o) ISSN 986-588 (o) STIRLING'S FORMULA AND ITS APPLICATION Šfkt Arslaagić Sarajvo B&H Abstract:

More information

EXST Regression Techniques Page 1

EXST Regression Techniques Page 1 EXST704 - Rgrssion Tchniqus Pag 1 Masurmnt rrors in X W hav assumd that all variation is in Y. Masurmnt rror in this variabl will not ffct th rsults, as long as thy ar uncorrlatd and unbiasd, sinc thy

More information

Computing and Communications -- Network Coding

Computing and Communications -- Network Coding 89 90 98 00 Computing and Communications -- Ntwork Coding Dr. Zhiyong Chn Institut of Wirlss Communications Tchnology Shanghai Jiao Tong Univrsity China Lctur 5- Nov. 05 0 Classical Information Thory Sourc

More information

22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches.

22/ Breakdown of the Born-Oppenheimer approximation. Selection rules for rotational-vibrational transitions. P, R branches. Subjct Chmistry Papr No and Titl Modul No and Titl Modul Tag 8/ Physical Spctroscopy / Brakdown of th Born-Oppnhimr approximation. Slction ruls for rotational-vibrational transitions. P, R branchs. CHE_P8_M

More information

ENGG 1203 Tutorial. Difference Equations. Find the Pole(s) Finding Equations and Poles

ENGG 1203 Tutorial. Difference Equations. Find the Pole(s) Finding Equations and Poles ENGG 03 Tutoial Systms ad Cotol 9 Apil Laig Obctivs Z tasfom Complx pols Fdbac cotol systms Ac: MIT OCW 60, 6003 Diffc Equatios Cosid th systm pstd by th followig diffc quatio y[ ] x[ ] (5y[ ] 3y[ ]) wh

More information

Thomas J. Osler. 1. INTRODUCTION. This paper gives another proof for the remarkable simple

Thomas J. Osler. 1. INTRODUCTION. This paper gives another proof for the remarkable simple 5/24/5 A PROOF OF THE CONTINUED FRACTION EXPANSION OF / Thomas J Oslr INTRODUCTION This ar givs aothr roof for th rmarkabl siml cotiud fractio = 3 5 / Hr is ay ositiv umbr W us th otatio x= [ a; a, a2,

More information

Introduction to Quantum Information Processing. Overview. A classical randomised algorithm. q 3,3 00 0,0. p 0,0. Lecture 10.

Introduction to Quantum Information Processing. Overview. A classical randomised algorithm. q 3,3 00 0,0. p 0,0. Lecture 10. Itroductio to Quatum Iformatio Procssig Lctur Michl Mosca Ovrviw! Classical Radomizd vs. Quatum Computig! Dutsch-Jozsa ad Brsti- Vazirai algorithms! Th quatum Fourir trasform ad phas stimatio A classical

More information

ECE594I Notes set 6: Thermal Noise

ECE594I Notes set 6: Thermal Noise C594I ots, M. odwll, copyrightd C594I Nots st 6: Thrmal Nois Mark odwll Uivrsity of Califoria, ata Barbara rodwll@c.ucsb.du 805-893-344, 805-893-36 fax frcs ad Citatios: C594I ots, M. odwll, copyrightd

More information

A Review of Complex Arithmetic

A Review of Complex Arithmetic /0/005 Rviw of omplx Arithmti.do /9 A Rviw of omplx Arithmti A omplx valu has both a ral ad imagiary ompot: { } ad Im{ } a R b so that w a xprss this omplx valu as: whr. a + b Just as a ral valu a b xprssd

More information

SOME IDENTITIES FOR THE GENERALIZED POLY-GENOCCHI POLYNOMIALS WITH THE PARAMETERS A, B AND C

SOME IDENTITIES FOR THE GENERALIZED POLY-GENOCCHI POLYNOMIALS WITH THE PARAMETERS A, B AND C Joural of Mathatical Aalysis ISSN: 2217-3412, URL: www.ilirias.co/ja Volu 8 Issu 1 2017, Pags 156-163 SOME IDENTITIES FOR THE GENERALIZED POLY-GENOCCHI POLYNOMIALS WITH THE PARAMETERS A, B AND C BURAK

More information

ONLINE SUPPLEMENT Optimal Markdown Pricing and Inventory Allocation for Retail Chains with Inventory Dependent Demand

ONLINE SUPPLEMENT Optimal Markdown Pricing and Inventory Allocation for Retail Chains with Inventory Dependent Demand Submittd to Maufacturig & Srvic Opratios Maagmt mauscript MSOM 5-4R2 ONLINE SUPPLEMENT Optimal Markdow Pricig ad Ivtory Allocatio for Rtail Chais with Ivtory Dpdt Dmad Stph A Smith Dpartmt of Opratios

More information

Investigation of Transition to Chaos for a Lotka. Volterra System with the Seasonality Factor Using. the Dissipative Henon Map

Investigation of Transition to Chaos for a Lotka. Volterra System with the Seasonality Factor Using. the Dissipative Henon Map Applid Mathmatical Scics, Vol. 9, 05, o. 7, 580-587 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.05.57506 Ivstigatio of Trasitio to Chaos for a Lotka Voltrra Systm with th Sasoality Factor Usig

More information

A Propagating Wave Packet Group Velocity Dispersion

A Propagating Wave Packet Group Velocity Dispersion Lctur 8 Phys 375 A Propagating Wav Packt Group Vlocity Disprsion Ovrviw and Motivation: In th last lctur w lookd at a localizd solution t) to th 1D fr-particl Schrödingr quation (SE) that corrsponds to

More information

Australian Journal of Basic and Applied Sciences, 4(9): , 2010 ISSN

Australian Journal of Basic and Applied Sciences, 4(9): , 2010 ISSN Australia Joural of Basic ad Applid Scics, 4(9): 4-43, ISSN 99-878 Th Caoical Product of th Diffrtial Equatio with O Turig Poit ad Sigular Poit A Dabbaghia, R Darzi, 3 ANaty ad 4 A Jodayr Akbarfa, Islaic

More information