Monotonization of flux, entropy and numerical schemes for conservation laws
|
|
- Candice Hodge
- 6 years ago
- Views:
Transcription
1 J Math Aal Appl wwwelsevercom/locate/jmaa Mootozato of flx, etropy ad mercal schemes for coservato laws Admrth a,, GD Veerappa Gowda a, Jérôme Jaffré b a TIFR Cetre, PO Box 134, Bagalore 56001, Ida b INRIA-Rocqecort, B P 105, Le Chesay Cedex, Frace Receved 31 March 008 Avalable ole 0 May 008 Sbmtted by V Radlesc Abstract Usg the cocept of mootozato, famles of two step ad -step fte volme schemes for scalar hyperbolc coservato laws are costrcted ad aalyzed These famles cota the FORCE scheme ad gve a alteratve to the MUSTA scheme These schemes ca be exteded to systems of coservato law Crow Copyrght 008 Pblshed by Elsever Ic All rghts reserved Keywords: Fte volmes; Fte dffereces; Rema solvers; Coservato laws; Mootozato 1 Itrodcto Let f : R R be a Lpschtz cotos fcto ad cosder the scalar coservato law t + f x = 0, t >0, x R, x, 0 = 0 x, x R, where 0 BVR L 1 loc R Ths problem has bee extesvely stded the last decade I geeral problem 11 ad 1 does ot admt reglar soltos becase of two reasos: The characterstcs do ot fll the etre space, gvg rase to empty regos where the soltos caot be determed by the tal data The characterstcs tersect ad lead to mltvaled soltos I order to overcome these dffcltes, the cocept of wea soltos s trodced To costrct sch soltos wth smple data, oe faces dffcltes ad I order to overcome, oe mae se of the varace property of Eq 11, that s t s varat der the trasformato x αx, t αt for ay α>0 Ths leads to a self smlar 11 1 * Correspodg athor E-mal addresses: adt@mathtfbgres Admrth, gowda@mathtfbgres GD Veerappa Gowda, jeromejaffre@rafr J Jaffré 00-47X/$ see frot matter Crow Copyrght 008 Pblshed by Elsever Ic All rghts reserved do:101016/jjmaa
2 48 Admrth et al / J Math Aal Appl solto the varable ξ = x/t s called the rarefacto wave Ths solto s ot determed by the tal data ad s sed to determe the solto the empty space I order to overcome, dscottes are trodced the regos where the characterstcs tersect Now sg the defto of wea soltos, t s possble to determe the les of dscotty called shocs Shocs mst satsfy the Rae Hgoot codto coectg the taget to the le of dscotty wth the jmps of the solto across t The ext problem s the oqeess of wea soltos Ths oqeess bascally comes from the way oe flls the empty rego by a solto Now by loog at the derlyg physcal pheomea a cocept of a Etropy crtero s trodced whch qely defes the solto the empty rego for smple data Usg the above cocepts, exstece of a qe etropy solto s proved for arbtrary data There are three fdametal methods sed to obta the exstece ad qeess of a etropy solto 1 The Hamlto Jacob method Here oe assmes that the flx f s C ad strctly covex ad cosders the Hamlto Jacob eqato: v t + fv x = 0, x R, t>0, 13 vx,0 = v 0 x, x R, 14 where v 0 x = x 0 0θ dθ Ths eqato has a qe vscosty solto ad a explct formla was gve by Hopf [] The lettg = x v, Lax ad Ole proved that s the qe etropy solto of Eqs 11, 1 [] The vashg vscosty method Here oe loos at the olear parabolc eqato t + f x = ε xx, x R, t>0, x, 0 = 0 x, x R Krzov [4] proves that there exsts a qe solto ε of Eqs 15, 16 covergg L 1 loc to a qe etropy solto of Eqs 11, 1 as ε 0 3 Nmercal schemes I ths method mercal schemes are derved sg space ad tme dscretzatos of Eqs 11, 1 These scheme calclate a approxmato solto whch coverges to the qe etropy solto Lax ad Fredrchs, Godov, Eqst ad Osher, Roe ad others cotrbted to ths approach I ths paper we cocetrate o mercal schemes to solve Eqs 11, 1 ad we wll costrct schemes whose mercal flxes ca be evalated by pot evalatos of the flx fcto f cotrarly to may mercal schemes whch mercal flx evalatos volve calclatos of tegrals, maxma or mma of f Ths property of sg oly pot evalatos of the mercal flx s crcal for extedg wthot too mch complexty a mercal scheme to systems I Secto we trodce the cocept of mootozato whch leads s to a ew defto of etropy solto Ths approach ca lead to the cocept of etropy for systems I Secto 3 we costrct a frst two step mootozato scheme whch s actally the Force scheme [5,6] I Secto 4 ths scheme s geeralzed to a famly of two step mootozato schemes ad aalyzed I Secto 5 these mercal schemes are exteded to a famly of -step mootozato schemes whch gves a alteratve to the MUSTA scheme [7] These schemes are easy to exted to systems Secto 6 Mootozato ad etropy A basc gredet stdyg a mercal scheme s the stdy of the Rema problem Let a,b,x 0 R ad let x = { a f x<x0, b f x x 0, 1 ad the solto set Ra,b,x 0 assocated to 1 s gve by Ra,b,x 0 = { ; s a wea solto of Eqs 11, 1 }
3 Admrth et al / J Math Aal Appl I geeral Ra,b,x 0 ca have more tha oe solto Ths set Ra,b,x 0 trs ot to be a mportat tool dervg fte volme schemes Ths s a well stded method for detals see [3] Let h>0, t > 0, = t/h ad dscretze the doma to dsjot rectagles R wth legth h ad breadth t That s for Z, x 0letR = I J where x +1/ = h, t = t, I =[x +1/,x +3/, J = [ t, + 1 t mst satsfy the CFL codto: let sp f θ 1, θ [ M,M] where M = 0 We dscretze 0 by { 0 } Z defed as 0 = 1 0 x dx h I ad we assme that for 0 j, { j } Z are ow I order to defe { +1 } Z, we choose a solto w R, +1,x +3/ for each Z ad defe wx,t = w x, t for x, t R The from the CFL codto, w s well defed ad s a solto of Eq 11 for x R, t<t<+ 1 t wth tal codto wx,t = for x I Now we defe { +1 } Z as +1 = 1 wx,t +1 dx h I Sce w satsfes 11 R t, + 1 t ad hece tegratg 11 over R to obta the followg formla +1 t +1 = 1 f wx +3/,t dt 1 +1 t f wx +1/,t dt 3 t t t The evalato of +1 from 3 depeds heavly o the choce of the Rema problem solto {w } Hece geeral dfferet choces of {w } gve rase to dfferet sets of { } I fact oe ca geerate ftely may L 1 -cotractve coverget schemes provded f has both creasg as well as decreasg parts [1] If the flx f s strctly mootoe the the characterstcs of Eq 11 do ot tersect the les x = x +1/ for t t<+ 1 t Hece for ay w R, +1,x +3/ { w x f f > 0, +3/,t= +1 f f < 0, ad scheme 3 redces to the stadard pstream scheme { +1 = f +1 f f f < 0, f f +1 f f 4 > 0 As a coseqece of ths, the scheme s depedet of the choce of the Rema data solto {w } ad coverges L 1 loc to the qe etropy solto If f s strctly covex ad the {w } are chose so that they satsfy the Lax Ole, Krzov etropy codto, the scheme 3 redces to the fte volme scheme +1 = F G +1, F G 1, 5 where F G a, b s the Godov flx defed by { F G mθ a,b fθ f a b, a, b = 6 max θ a,b fθ f a b t
4 430 Admrth et al / J Math Aal Appl I fact from a theorem of Ole see [3], eve f f s ot covex, the Godov scheme 5, 6 coverges L 1 loc to the qe etropy solto of problem 11, 1 Besdes ts optmal propertes terms of mercal dffso, a drawbac of the Godov scheme s that ts mercal flx 6 caot be wrtte terms of pot vales of the fcto f, a pot whch becomes crtcal whe extedg the method to systems O the other had we otce from scheme 4 that f the flx s mootoe, the the choce of the Rema problem solto s rrelevat ad the flx ca be calclated terms of pot vales of f Therefore we covert problem 11 to a problem havg a mootoe flx fcto Ths procedre s called mootozato Gve M>0, α R, deote f α by f α = f /α ad choose α sch that sp [ M,M] f < α Let be a solto of Eqs 11, 1 wth 0 M, ad cosder the chage of varables x = X + ατ, t = τ, x,t = vx,τ The v satsfes v τ + f 1/α v X = 0 for X R, τ>0, 8 vx,0 = 0 X for X R 9 Frthermore vx,0 = 0 x M ad from 7, f 1 v = fv αv s a strctly mootoe fcto α for v [ M,M] Hece the fte volme scheme for Eqs 8, 9 does ot deped o the choce of the Rema data solto Frthermore t prodces a solto v h whch coverges L 1 loc to the qe etropy solto v of problem 8, 9 Therefore x, t = vx αt,t s the qe etropy solto for problem 11, 1 Coseqetly we ca state the followg alteratve defto of the etropy solto Defto Etropy solto Let L 1 loc L be a wea solto of problem 11, 1 The s sad to be a etropy solto to ths problem, f x, t = vx αt,t for all α sch that f 1/α s strctly mootoe [ 0, 0 ] ad v s the qe solto of problem 8, 9 obtaed after covergece of the solto of the pstream fte volme scheme 4 appled to problem 8, 9 I the above aalyss we chage the varables so that the ew varables, the flx fcto becomes strctly mootoe Ths allows s to redce the fte volme scheme o rectaglar space-tme meshes to a smple pstream mercal scheme Now the ext secto we reverse the order, amely we eep the eqato as t s bt chage the rectaglar mesh to parallelogram meshes to obta a mercal scheme whch les betwee Godov ad Lax Fredrchs schemes terms of mercal vscosty 3 A frst two step mootozato scheme 31 Formlato of the two step mootozato scheme We assme aga that the tal data satsfes 0 [ M,M] for some M>0ad we trodce some more otato x = + 1/h, t +1/ = + 1/ t, p = x +1/, t, p +1/ = x,+ 1/ t, P +1/ = parallelogram wth vertces p,p +1,p+1/ +1,p +1/, P = parallelogram wth vertces p +1/,p +1 +1,p+1,p +1/ 1, asshowfg31 We assme that all the characterstcs emaatg from p respectvely p +1/ ], [p 1,p+1/ ] respectvely [p +1/ ], [p+1/ [p,p+1/ sp [ M,M] 1 f 1,p ,p +1 7 do ot tersect the le segmets ] Ths mples the followg codto 31
5 Admrth et al / J Math Aal Appl Fg 31 Notato for the two step mootozato scheme Wth the above otato ad assmpto, we ca ow derve the two step mootozato scheme Assme that { } Z for 0, are gve wth [ M,M] As Secto let w R, +1,x +3/ whch eed ot be a etropy solto be ay solto ad defe wx,t = w +1/ x, t for x, t P The from codto 31, w s a well-defed wea solto ad let +1/ = 1 h x +1 x w x, + 1/ t dx Mass coservato the cells gves 0 = wt + fw x dxdt = P +1/ P +1/ wνt + fwν x ds Evalatg the tegral o the bodary of P +1/ ad sg the CFL codto 31 characterstcs do ot tersect the le segmets, see Fg 31 we obta +1/ = = [ = t p +1/ +1 p +1 [ f fw 1 w dt 1 t [ f +1 f ] p +1/ p f 1 fw 1 ] w dt ]
6 43 Admrth et al / J Math Aal Appl Now repeatg the argmet wth data { +1/ } at t +1/ ad +1 = h 1 x+3/ x +1/ wx, + 1 t dx we have +1 = +1/ 1 [ f +1/ = +1/ / +1/ [ f +1/ Ths the two step mootozato scheme reads +1/ = + +1 [ ] f +1 f, +1 = +1/ / [ f +1/ f +1/ 1 f +1/ 1 f +1/ 1 ] +1/ ] 1 ] 3 Observe that there s a bacward shft evalatg +1 ad that t eeds oly pot evalatos of the flx fcto f The two step scheme 3 was already trodced ad aalyzed [5,6] ad t ca be wrtte a compact form as follows For a,b R let Ha,b= a f b f a = a + b fb fa 33 The scheme 3 ca be rewrtte as or +1/ = [ f +1 f ], +1 = +1/ 1 [ f +1/ +1/ = H, +1, +1 +1/] f 1, 34 = H +1/ 1, +1/ so we formlate the two step mootozato scheme the compact form = H H 1,,H, Covergece of the two step mootozato scheme Cocerg covergece we have the ma reslt Theorem 31 Let 0 BVR ad M The der the CFL codto 31 the two step fte volme scheme { } gve 35 coverges to the qe etropy solto Proof Let a,b [ M,M], the from 31 we have H a a, b = f a 0,, H b a, b = 1 1 f b 0 36 ad hece H s a odecreasg fcto each of ts argmet Therefore from 35 the scheme s a three pot mootoe scheme Let gx,y,z = HHX,Y,HY,Z, the gx, X, X = H HX,X,HX,X = HX,X= X 37 The scheme s L -stable, sce, whe assmg [ M,M] for all Z, from 36 we ca wrte M = g M, M, M g 1,, +1 = +1 gm,m,m = M
7 Admrth et al / J Math Aal Appl Fally let s wrte the scheme coservatve form Expadg 35 we obta +1 f H, +1 f H 1, = H 1, = 1 [ f + f H, +1 f 1 f H 1, ] = [ f + f H, +1 + f 1 f H 1, ] 1 Therefore +1 = [ F, +1 F 1, ] 38 where the mercal flx F a, b s gve by F a, b = 1 [ ] a f a + f Ha,b + = 1 [ fa+ f Ha,b Ha,b + a ] = 1 [ fa+ f Ha,b b a + 1 ] fb fa, or F a, b = 1 [ fa+ fb+ f Ha,b + a b ] 39 4 From 37 F a, a = fa so the flx s cosstet ad coseqetly the solto of the two step mootozato scheme 3 whch ca be wrtte alteratvely as 33, 35 or 38, 39 coverges to the qe etropy solto of problem 11, 1 Ths proves the theorem 33 Comparso wth the Lax Fredrchs LF ad the two step Lax Wedroff Rchtzer LWR scheme O oe had the two step mootozato scheme 38, 39 gves +1 = [ f f H, +1 f 1 f H 1, ] 310 O the other had the two step LWR scheme pt α = β = 1/ Eq 19 of [3] s gve by w +1 = f H +1, f H 1,, whle the LF scheme reads v +1 = f +1 f 1 It follows that +1 = w+1 + v +1 Hece the solto gve by scheme 38, 39 s the average of that gve by the LF ad LWR schemes Ths remar was already made by Toro [5] Therefore eve thogh the LWR scheme s ot L -stable, by tag ts average wth the L -stable LF scheme we obta a L -stable coverget scheme I terms of mercal vscosty, the mercal vscosty coeffcet Q +1/ of the two step mootozato scheme 38, 39 s determed by Hece F a, b = 1 fa+ fb Q +1/ b a
8 434 Admrth et al / J Math Aal Appl Fg 3 Comparso of the Godov, Lax Fredrch ad the two step mootozato scheme for f= / wth tal codto x, 0 = f x<0ad1fx>0 The solto s show at t = 1 ad was calclated wth h = /100, t = /300 Therefore b a Q +1/ = Q +1/ = fa+ fb F a, b = fa+ fb 1 fa+ fb+ f Ha,b + a b = 1 a b fa+ fb f Ha,b = 1 fa+ fb f a f b f a a b = 1 fa+ fb fa+ f ξ f b f a a b = 1 fb fa + f ξ fb fa b a f ξ + b a = f ξ fb fa f ξ b a 1 + f ξ fb fa b a ad QLF +1/ Let f= ad deote by Q G +1/ Fredrchs schemes respectvely The we have Q G +1/ = 1 + = Q +1/ 1 = Q LF +1/ f ξ the mercal vscosty coeffcet of the Godov ad the Lax Ths shows that the performace of scheme 38, 39 s better tha the Lax Fredrchs scheme terms of mercal vscosty as ca be observed o Fg 3 4 Geeralzed two step mootozato schemes There are may ways to geeralze the two step mootozato preseted the prevos secto I ths secto we geeralze t to a famly of two step schemes Let γ 1,γ [0, 1] satsfyg γ 1 + γ = 1 ad β 1,β [ 1, 1] Gve the dscretzato steps h, t of space ad tme, we frther dscretze tme by dvdg the tme step to two sbsteps γ 1 t, γ t, ad we move the space dscretzato pot p to p +1/ by legth β 1 h at tme t + γ 1 t ad frther move p +1/ by legth β h bac to oe of the dscretzato pots at tme t + γ 1 + γ t = t +1 See Fg 41 for γ 1 = 1/3, γ = /3, β 1 = 1/, β = 1/ ad Fg 31 for γ 1 = γ = 1/, β 1 = β = 1/ I ths way we bld le segmets whch, addto of the les t = t, t = γ 1 t, t = t +1 wll form the bodares of the cotrol volmes for the two step fte volme sheme
9 Admrth et al / J Math Aal Appl Fg 41 Cotrol volmes for a geeralzed two step mootozato scheme wth γ 1 = 1/3, γ = /3, β 1 = 1/, β = 1/ γ l,β l, l = 1,, are chose also order to satsfy the CFL codto γ l sp f m β l, 1 β l, l = 1,, 41 [ M,M] order to esre that, for l = 1, the characterstcs leavg p, ad for l =, that leavg p+1/ do ot tersect the le segmets For l = 1,, let δ l = γ l β l δ 1 s the slope of the segmet [p,p+1/ ] ad δ s the slope of the segmet coectg p +1/ to oe of the dscretzato pots at tme t +1 For a,b R defe { a γl f δl b f δl a f δ l > 0, H δl a, b = l = 1, 4 b γ l f δl b f δl a f δ l < 0, We ca geerate for dfferet famles of coverget schemes, depedg o the sgs of the β s Scheme 1 β 1 0, β 0, β 1 + β = 1 If M, from the CFL codto 41, Scheme 1 reads +1/ = H δ1, +1 = γ 1 f δ1 +1 fδ1, +1/ = H δ 1, +1/ +1/ = 1 γ +1/ +1/ f δ fδ 1 +1 Note that the case β l = γ l = 1/, l = 1,, correspods to the two step scheme preseted the prevos secto Scheme β 1 > 0, β < 0 wth β 1 = β
10 436 Admrth et al / J Math Aal Appl If M, der the CFL codto 41, Scheme reads +1/ = H δ1, +1 = γ 1 f δ1 +1 fδ1, +1/ = H δ 1, +1/ +1/ = γ +1/ f δ +1 fδ +1/ 1 Ths case correspods to the stato show Fg 41 The other two cases are β 1 0, β 0, β 1 + β = 1 ad β 1 < 0, β > 0, β = β 1 ad they ca be dealt exactly as above 5 Geeralzed -step mootozato schemes We ow geeralze the method to steps Let 1 be a teger ad for l = 1,,,let0 γ l 1 satsfyg l=1 γ l = 1 We trodce sbtervals of t,t +1 deoted by [t + l,t + l+1 ], l = 0,, 1, wth t + l = t + l l=1 γ l t, l = 1,, Let X 1 <X <X 3 be ay three cosectve space dscretzato pots Ths they satsfy X 3 X = X X 1 = h We ow trodce admssble crves ρ :[t,t +1 ] R s sad to be a admssble crve f 1 ρ s cotos ad ρt = X, ρ [t + l,t + l+1 ] s a le segmet for 0 l 1, 3 ρt +1 {X 1,X,X 3 } Examples of admssble crves are show Fgs 31, 41, 51, 5 Deote ΓX 1,X,X 3,γ 1,,γ,= { ρ : [t,t +1, ] [X 1,X 3 ]; ρ s admssble }, Γ + X 1,X,X 3,γ 1,,γ,= { ρ ΓX 1,X,X 3,γ 1,,γ,; ρt +1 = X 3 }, Γ 0 X 1,X,X 3,γ 1,,γ,= { ρ ΓX 1,X,X 3,γ 1,,γ,; ρt +1 = X }, Γ X 1,X,X 3,γ 1,,γ,= { ρ ΓX 1,X,X 3,γ 1,,γ,; ρt +1 = X 1 } For ρ ΓX 1,X,X 3,γ 1,,γ,we deote by δ l,l= 1,, the slopes of the le segmets of ρ o the terval [t + l,t + l+1 ], l = 0,, 1, ad the assocated β l are defed by β l = γ l δ l For each Z let ρ Γx 1/,x +1/,x +3/,γ 1,,γ,satsfyg j {, 0, +} sch that ρ Γ j x 1/,x +1/,x +3/,γ 1,,γ, Z The slopes of the ρ s are the same for all s ad are deoted by δ 1,,δ The ρ s wll be the lateral bodares of the cotrol volmes sed to defe the fte volme scheme We assme that {ρ } Z satsfy the CFL codto sp f m β l,1 β l for 1 l 51 γ l [ M,M] Wth the otatos as 4 we ca ow defe the -step scheme as follows Gve { } wth M, defe dctvely for 1 l 1, l 1 l 1 + l + + H δl,+1 f δ l > 0, = l = 1,, 5 l 1 l H δl, f δ l < 0, 1
11 Admrth et al / J Math Aal Appl Fg 51 Cotrol volmes for a 3-step mootozato scheme, γ 1 = γ = γ 3 = 1 3, β 1 = 1 3, β = 5 6, β 3 = 1 ρ Γ x 1/,x +1/,x +3/,γ 1,γ,γ 3, Fg 5 Cotrol volmes for a 3-step mootozato scheme, γ 1 = γ = γ 3 = 1 3, β 1 = 1, β = 1 3, β 3 = 5 6 ρ Γ + x 1/,x +1/,x +3/,γ 1,γ,γ 3,
12 438 Admrth et al / J Math Aal Appl The +1 = H δ H δ H δ H δ , f ρ t +1 = x +3/, +,+1 f ρ t +1 = x 1/, +, f ρ t +1 = x +1/ ad δ < 0, +,+1 f ρ t +1 = x +1/ ad δ > 0 As Theorem 31, der the CFL codto 51, t follows easly that H δl a, b s mootoe each of ts varable ad H δl a, a = a Hece the scheme 5 ad 53 coverges to a qe etropy solto of problem 11, 1 f 0 M ad 0 BVR Example 1 If δ l 0, l = 1,,, the scheme 5, 53 ca be wrtte as follows Defe for l 3, H X 1,X,X 3 = H δ Hδ1 X 1,X, H δ1 X,X 3, H l X 1,X,,X l+1 = H δl H l 1 X 1,,X l, H l 1 X,,X l+1, ad FX 1,,X = γ 1 f δ1 X 1 + γ f δ H1 X 1,X X 1 + γ l+1 f δl+1 H l X 1,,X l+1 54 l= The +1 = F, +1 +, F 1, + 55 If =, β l = γ l = 1 the scheme 55 cocdes wth scheme 38, 39 If β l = γ l = 1 for 1 l, the the CFL codto 51 gves sp f 1 m [ M,M], 1 1 = 1 Hece the CFL codto reads ow sp [ M,M] f 1 If =, δ l > 0, l = 1,, the scheme 55 ca be wrtte as +1/ = H δ1, +1 = γ 1 f δ1 +1 fδ1 = 1 β 1 + β 1 +1 γ 1 f +1 f, +1 = 1 β +1/ 1 + β +1/ γ f +1/ +1/ f 1 Frthermore f we let β 1 = β = 1, γ 1 = 3 4, γ = 1 4, the the CFL codto 51 becomes sp f /3 [ M,M] We cosder ow the case whe the slopes δ l s chage sg Let = 3, γ 1 + γ + γ 3 = 1, β 1 = β + β 3 wth β 0, β 3 0, the Let +1/3 +/3 = γ 1 f δ1 +1 fδ1, = +1/3 γ +1/3 +1/3 f δ fδ 1, = +/3 γ 3 +/3 +/3 f δ3 fδ FX 1,X,X 3 = γ 1 f δ1 X 3 + γ f δ Hδ1 X,X 3 + γ 3 f δ3 Hδ Hδ1 X 1,X, H δ1 X,X 3, the the scheme reads +1 = F 1, +1, F, 1, 53
13 Admrth et al / J Math Aal Appl Exteso to systems Cosder a hyperbolc system of coservato laws U t + FU x = 0, x R, t>0, Ux,0 = U 0, x R, where U s a -vector ad F : R R a C 1 -map For α R let X = x + αt, τ = t, VX,τ= Ux,t The V satsfes 61 6 V τ + F V αv X = 0, X R, τ>0, 63 VX,0 = U 0 X, X R 64 If U s a egevale of F U, the U α s a egevale of F U αi Hece f the egevales of F U are boded, the we ca choose α large eogh sch that all the egevales correspodg to 63 are postve Therefore, f we have a L -bod for a solto of 61, 6 the we ca covert t to a solto of 63, 64 wth all egevales postve Frthermore f we defe F α U = FU U α for α 0, the we ca defe the scheme 34 for the system 61, 6 provded that all the waves are trapped as before I the same way -step schemes ca be defed for systems Ther advatage s that they are pot evalato schemes Oe ca expect a better accracy by gog to -step schemes ad choosg proper γ l s ad δ l s Ths may also exted to the mltdmesoal case ad wth a dffso term o the rght-had sde 7 Coclso Usg the techqe of mootozato we showed how to costrct a famly of mltstep schemes wth oly pot vale evalatos of the flx fcto Ths famly cldes the Force ad proposes a alteratve for the Msta schemes For all these schemes we proved covergece of the approxmate solto to the etropy solto of the cotos problem We also gave hts o how to exted them to systems ad hgh resolto schemes I forthcomg papers we wll exted these schemes to hgher resolto schemes ad to the dscotos flx case We wll also gve a example of applcato to a system of coservato laws represetg a problem of polymer floodg Acowledgmet The athors acowledge fdg from Ido-Frech Cetre for Promoto of Advaced Research der Project Refereces [1] Admrth, S Mshra, GD Veerappa Gowda, Optmal etropy soltos for coservato laws wth dscotos flx-fctos, J Hyperbolc Dffer Eq [] LC Evas, Partal Dfferetal Eqatos, Grad Std Math, vol 19, Amerca Mathematcal Socety, 00 [3] E Godlews, P-A Ravart, Hyperbolc Systems of Coservato Laws, Trmestvell, 1991 [4] SN Krzov, Frst order qaslear eqatos several depedet varables, Math USSR Sb [5] EF Toro, Rema Solvers ad Nmercal Methods for Fld Dyamcs, Sprger-Verlag, 1999 [6] EF Toro, SJ Bllet, Cetered TVD schemes for hyperbolc coservato laws, IMA J Nmer Aal [7] EF Toro, MUSTA: A mlt-stage mercal flx, Appl Nmer Math
u(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )):
x, t ), h x The Frst-Order Wave Eqato The frst-order wave advecto) eqato s c > 0) t + c x = 0, x, t = 0) = 0x). The solto propagates the tal data 0 to the rght wth speed c: x, t) = 0 x ct). Ths Rema varat
More informationu(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )):
x, t, h x The Frst-Order Wave Eqato The frst-order wave advecto eqato s c > 0 t + c x = 0, x, t = 0 = 0x. The solto propagates the tal data 0 to the rght wth speed c: x, t = 0 x ct. Ths Rema varat s costat
More informationB-spline curves. 1. Properties of the B-spline curve. control of the curve shape as opposed to global control by using a special set of blending
B-sple crve Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last pdated: Yeh-Lag Hs (--9). ote: Ths s the corse materal for ME Geometrc modelg ad compter graphcs, Ya Ze Uversty. art of ths materal
More informationThe Finite Volume Method for Solving Systems. of Non-linear Initial-Boundary. Value Problems for PDE's
Appled Matematcal Sceces, Vol. 7, 13, o. 35, 1737-1755 HIKARI Ltd, www.m-ar.com Te Fte Volme Metod for Solvg Systems of No-lear Ital-Bodary Vale Problems for PDE's 1 Ema Al Hssa ad Zaab Moammed Alwa 1
More informationBeam Warming Second-Order Upwind Method
Beam Warmg Secod-Order Upwd Method Petr Valeta Jauary 6, 015 Ths documet s a part of the assessmet work for the subject 1DRP Dfferetal Equatos o Computer lectured o FNSPE CTU Prague. Abstract Ths documet
More information2.160 System Identification, Estimation, and Learning Lecture Notes No. 17 April 24, 2006
.6 System Idetfcato, Estmato, ad Learg Lectre Notes No. 7 Aprl 4, 6. Iformatve Expermets. Persstece of Exctato Iformatve data sets are closely related to Persstece of Exctato, a mportat cocept sed adaptve
More informationDISTURBANCE TERMS. is a scalar and x i
DISTURBANCE TERMS I a feld of research desg, we ofte have the qesto abot whether there s a relatoshp betwee a observed varable (sa, ) ad the other observed varables (sa, x ). To aswer the qesto, we ma
More informationNon-uniform Turán-type problems
Joural of Combatoral Theory, Seres A 111 2005 106 110 wwwelsevercomlocatecta No-uform Turá-type problems DhruvMubay 1, Y Zhao 2 Departmet of Mathematcs, Statstcs, ad Computer Scece, Uversty of Illos at
More informationSummary of the lecture in Biostatistics
Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the
More information{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:
Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed
More informationResearch Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings
Hdaw Publshg Corporato Iteratoal Joural of Mathematcs ad Mathematcal Sceces Volume 009, Artcle ID 391839, 9 pages do:10.1155/009/391839 Research Artcle A New Iteratve Method for Commo Fxed Pots of a Fte
More informationFunctions of Random Variables
Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,
More informationCubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem
Joural of Amerca Scece ;6( Cubc Nopolyomal Sple Approach to the Soluto of a Secod Order Two-Pot Boudary Value Problem W.K. Zahra, F.A. Abd El-Salam, A.A. El-Sabbagh ad Z.A. ZAk * Departmet of Egeerg athematcs
More information( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix.
Revew + v, + y = v, + v, + y, + y, Cato! v, + y, + v, + y geeral Let A be a atr Let f,g : Ω R ( ) ( ) R y R Ω R h( ) f ( ) g ( ) ( ) ( ) ( ( )) ( ) dh = f dg + g df A, y y A Ay = = r= c= =, : Ω R he Proof
More informationMu Sequences/Series Solutions National Convention 2014
Mu Sequeces/Seres Solutos Natoal Coveto 04 C 6 E A 6C A 6 B B 7 A D 7 D C 7 A B 8 A B 8 A C 8 E 4 B 9 B 4 E 9 B 4 C 9 E C 0 A A 0 D B 0 C C Usg basc propertes of arthmetc sequeces, we fd a ad bm m We eed
More information. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1)
Chapter 7 Fuctos o Bouded Varato. Subject: Real Aalyss Level: M.Sc. Source: Syed Gul Shah (Charma, Departmet o Mathematcs, US Sargodha Collected & Composed by: Atq ur Rehma (atq@mathcty.org, http://www.mathcty.org
More informationThe Mathematical Appendix
The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.
More informationX ε ) = 0, or equivalently, lim
Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece
More informationLecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model
Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The
More informationSolving Constrained Flow-Shop Scheduling. Problems with Three Machines
It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632
More informationChapter 5 Properties of a Random Sample
Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample
More informationMeromorphic Solutions of Nonlinear Difference Equations
Mathematcal Comptato Je 014 Volme 3 Isse PP.49-54 Meromorphc Soltos of Nolear Dfferece Eatos Xogyg L # Bh Wag College of Ecoomcs Ja Uversty Gagzho Gagdog 51063 P.R.Cha #Emal: lxogyg818@163.com Abstract
More informationA Remark on the Uniform Convergence of Some Sequences of Functions
Advaces Pure Mathematcs 05 5 57-533 Publshed Ole July 05 ScRes. http://www.scrp.org/joural/apm http://dx.do.org/0.436/apm.05.59048 A Remark o the Uform Covergece of Some Sequeces of Fuctos Guy Degla Isttut
More information828. Piecewise exact solution of nonlinear momentum conservation equation with unconditional stability for time increment
88. Pecewse exact solto of olear mometm coservato eqato wth codtoal stablty for tme cremet Chaghwa Jag, Hyoseob Km, Sokhwa Cho 3, Jho Km 4 Korea Itellectal Property Offce, Daejeo, Korea, 3 Kookm Uversty,
More informationComplete Convergence and Some Maximal Inequalities for Weighted Sums of Random Variables
Joural of Sceces, Islamc Republc of Ira 8(4): -6 (007) Uversty of Tehra, ISSN 06-04 http://sceces.ut.ac.r Complete Covergece ad Some Maxmal Iequaltes for Weghted Sums of Radom Varables M. Am,,* H.R. Nl
More informationCS286.2 Lecture 4: Dinur s Proof of the PCP Theorem
CS86. Lecture 4: Dur s Proof of the PCP Theorem Scrbe: Thom Bohdaowcz Prevously, we have prove a weak verso of the PCP theorem: NP PCP 1,1/ (r = poly, q = O(1)). Wth ths result we have the desred costat
More informationEntropy ISSN by MDPI
Etropy 2003, 5, 233-238 Etropy ISSN 1099-4300 2003 by MDPI www.mdp.org/etropy O the Measure Etropy of Addtve Cellular Automata Hasa Aı Arts ad Sceces Faculty, Departmet of Mathematcs, Harra Uversty; 63100,
More informationLecture 3 Probability review (cont d)
STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto
More informationProcessing of Information with Uncertain Boundaries Fuzzy Sets and Vague Sets
Processg of Iformato wth Ucerta odares Fzzy Sets ad Vage Sets JIUCHENG XU JUNYI SHEN School of Electroc ad Iformato Egeerg X'a Jaotog Uversty X'a 70049 PRCHIN bstract: - I the paper we aalyze the relatoshps
More informationPart 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971))
art 4b Asymptotc Results for MRR usg RESS Recall that the RESS statstc s a specal type of cross valdato procedure (see Alle (97)) partcular to the regresso problem ad volves fdg Y $,, the estmate at the
More informationMotion Estimation Based on Unit Quaternion Decomposition of the Rotation Matrix
Moto Estmato Based o Ut Qatero Decomposto of the Rotato Matrx Hag Y Ya Baozog (Isttte of Iformato Scece orther Jaotog Uversty Bejg 00044 PR Cha Abstract Based o the t qatero decomposto of rotato matrx
More informationA Study on Generalized Generalized Quasi hyperbolic Kac Moody algebra QHGGH of rank 10
Global Joural of Mathematcal Sceces: Theory ad Practcal. ISSN 974-3 Volume 9, Number 3 (7), pp. 43-4 Iteratoal Research Publcato House http://www.rphouse.com A Study o Geeralzed Geeralzed Quas (9) hyperbolc
More informationIntroduction to local (nonparametric) density estimation. methods
Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest
More information18.413: Error Correcting Codes Lab March 2, Lecture 8
18.413: Error Correctg Codes Lab March 2, 2004 Lecturer: Dael A. Spelma Lecture 8 8.1 Vector Spaces A set C {0, 1} s a vector space f for x all C ad y C, x + y C, where we take addto to be compoet wse
More informationDiscrete Adomian Decomposition Method for. Solving Burger s-huxley Equation
It. J. Cotemp. Math. Sceces, Vol. 8, 03, o. 3, 63-63 HIKARI Ltd, www.m-har.com http://dx.do.org/0.988/jcms.03.3570 Dscrete Adoma Decomposto Method for Solvg Brger s-hxley Eqato Abdlghafor M. Al-Rozbaya
More information1 Onto functions and bijections Applications to Counting
1 Oto fuctos ad bectos Applcatos to Coutg Now we move o to a ew topc. Defto 1.1 (Surecto. A fucto f : A B s sad to be surectve or oto f for each b B there s some a A so that f(a B. What are examples of
More informationChapter 4 Multiple Random Variables
Revew for the prevous lecture: Theorems ad Examples: How to obta the pmf (pdf) of U = g (, Y) ad V = g (, Y) Chapter 4 Multple Radom Varables Chapter 44 Herarchcal Models ad Mxture Dstrbutos Examples:
More informationAn Expansion of the Derivation of the Spline Smoothing Theory Alan Kaylor Cline
A Epaso of the Derato of the Sple Smoothg heory Ala Kaylor Cle he classc paper "Smoothg by Sple Fctos", Nmersche Mathematk 0, 77-83 967) by Chrsta Resch showed that atral cbc sples were the soltos to a
More information1 Lyapunov Stability Theory
Lyapuov Stablty heory I ths secto we cosder proofs of stablty of equlbra of autoomous systems. hs s stadard theory for olear systems, ad oe of the most mportat tools the aalyss of olear systems. It may
More informationJournal of Mathematical Analysis and Applications
J. Math. Aal. Appl. 365 200) 358 362 Cotets lsts avalable at SceceDrect Joural of Mathematcal Aalyss ad Applcatos www.elsever.com/locate/maa Asymptotc behavor of termedate pots the dfferetal mea value
More informationLaboratory I.10 It All Adds Up
Laboratory I. It All Adds Up Goals The studet wll work wth Rema sums ad evaluate them usg Derve. The studet wll see applcatos of tegrals as accumulatos of chages. The studet wll revew curve fttg sklls.
More informationρ < 1 be five real numbers. The
Lecture o BST 63: Statstcal Theory I Ku Zhag, /0/006 Revew for the prevous lecture Deftos: covarace, correlato Examples: How to calculate covarace ad correlato Theorems: propertes of correlato ad covarace
More informationChapter 9 Jordan Block Matrices
Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.
More informationTESTS BASED ON MAXIMUM LIKELIHOOD
ESE 5 Toy E. Smth. The Basc Example. TESTS BASED ON MAXIMUM LIKELIHOOD To llustrate the propertes of maxmum lkelhood estmates ad tests, we cosder the smplest possble case of estmatg the mea of the ormal
More informationUNIT 2 SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS
Numercal Computg -I UNIT SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS Structure Page Nos..0 Itroducto 6. Objectves 7. Ital Approxmato to a Root 7. Bsecto Method 8.. Error Aalyss 9.4 Regula Fals Method
More informationCHAPTER 3 POSTERIOR DISTRIBUTIONS
CHAPTER 3 POSTERIOR DISTRIBUTIONS If scece caot measure the degree of probablt volved, so much the worse for scece. The practcal ma wll stck to hs apprecatve methods utl t does, or wll accept the results
More informationDerivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations
Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat
More informationhp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations
HP 30S Statstcs Averages ad Stadard Devatos Average ad Stadard Devato Practce Fdg Averages ad Stadard Devatos HP 30S Statstcs Averages ad Stadard Devatos Average ad stadard devato The HP 30S provdes several
More informationThe Primitive Idempotents in
Iteratoal Joural of Algebra, Vol, 00, o 5, 3 - The Prmtve Idempotets FC - I Kulvr gh Departmet of Mathematcs, H College r Jwa Nagar (rsa)-5075, Ida kulvrsheora@yahoocom K Arora Departmet of Mathematcs,
More informationTHE COMPLETE ENUMERATION OF FINITE GROUPS OF THE FORM R 2 i ={R i R j ) k -i=i
ENUMERATON OF FNTE GROUPS OF THE FORM R ( 2 = (RfR^'u =1. 21 THE COMPLETE ENUMERATON OF FNTE GROUPS OF THE FORM R 2 ={R R j ) k -= H. S. M. COXETER*. ths paper, we vestgate the abstract group defed by
More informationEconometric Methods. Review of Estimation
Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators
More informationMultiple Choice Test. Chapter Adequacy of Models for Regression
Multple Choce Test Chapter 06.0 Adequac of Models for Regresso. For a lear regresso model to be cosdered adequate, the percetage of scaled resduals that eed to be the rage [-,] s greater tha or equal to
More informationLecture 2: The Simple Regression Model
Lectre Notes o Advaced coometrcs Lectre : The Smple Regresso Model Takash Yamao Fall Semester 5 I ths lectre we revew the smple bvarate lear regresso model. We focs o statstcal assmptos to obta based estmators.
More informationAlternating Direction Implicit Method
Alteratg Drecto Implct Method Whle dealg wth Ellptc Eqatos the Implct form the mber of eqatos to be solved are N M whch are qte large mber. Thogh the coeffcet matrx has may zeros bt t s ot a baded system.
More informationSimulation Output Analysis
Smulato Output Aalyss Summary Examples Parameter Estmato Sample Mea ad Varace Pot ad Iterval Estmato ermatg ad o-ermatg Smulato Mea Square Errors Example: Sgle Server Queueg System x(t) S 4 S 4 S 3 S 5
More informationComputational Geometry
Problem efto omputatoal eometry hapter 6 Pot Locato Preprocess a plaar map S. ve a query pot p, report the face of S cotag p. oal: O()-sze data structure that eables O(log ) query tme. pplcato: Whch state
More informationC.11 Bang-bang Control
Itroucto to Cotrol heory Iclug Optmal Cotrol Nguye a e -.5 C. Bag-bag Cotrol. Itroucto hs chapter eals wth the cotrol wth restrctos: s boue a mght well be possble to have scotutes. o llustrate some of
More informationC-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory
ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?
More informationLecture 12 APPROXIMATION OF FIRST ORDER DERIVATIVES
FDM: Appromato of Frst Order Dervatves Lecture APPROXIMATION OF FIRST ORDER DERIVATIVES. INTRODUCTION Covectve term coservato equatos volve frst order dervatves. The smplest possble approach for dscretzato
More informationA scalar t is an eigenvalue of A if and only if t satisfies the characteristic equation of A: det (A ti) =0
Chapter 5 a glace: Let e a lear operator whose stadard matrx s wth sze x. he, a ozero vector x s sad to e a egevector of ad f there exsts a scalar sch that (x) x x. he scalar s called a egevale of (or
More informationL5 Polynomial / Spline Curves
L5 Polyomal / Sple Curves Cotets Coc sectos Polyomal Curves Hermte Curves Bezer Curves B-Sples No-Uform Ratoal B-Sples (NURBS) Mapulato ad Represetato of Curves Types of Curve Equatos Implct: Descrbe a
More informationNumerical Analysis Formulae Booklet
Numercal Aalyss Formulae Booklet. Iteratve Scemes for Systems of Lear Algebrac Equatos:.... Taylor Seres... 3. Fte Dfferece Approxmatos... 3 4. Egevalues ad Egevectors of Matrces.... 3 5. Vector ad Matrx
More informationOn the convergence of derivatives of Bernstein approximation
O the covergece of dervatves of Berste approxmato Mchael S. Floater Abstract: By dfferetatg a remader formula of Stacu, we derve both a error boud ad a asymptotc formula for the dervatves of Berste approxmato.
More informationarxiv:math/ v1 [math.gm] 8 Dec 2005
arxv:math/05272v [math.gm] 8 Dec 2005 A GENERALIZATION OF AN INEQUALITY FROM IMO 2005 NIKOLAI NIKOLOV The preset paper was spred by the thrd problem from the IMO 2005. A specal award was gve to Yure Boreko
More informationECONOMETRIC THEORY. MODULE VIII Lecture - 26 Heteroskedasticity
ECONOMETRIC THEORY MODULE VIII Lecture - 6 Heteroskedastcty Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur . Breusch Paga test Ths test ca be appled whe the replcated data
More informationPROJECTION PROBLEM FOR REGULAR POLYGONS
Joural of Mathematcal Sceces: Advaces ad Applcatos Volume, Number, 008, Pages 95-50 PROJECTION PROBLEM FOR REGULAR POLYGONS College of Scece Bejg Forestry Uversty Bejg 0008 P. R. Cha e-mal: sl@bjfu.edu.c
More informationMaps on Triangular Matrix Algebras
Maps o ragular Matrx lgebras HMED RMZI SOUROUR Departmet of Mathematcs ad Statstcs Uversty of Vctora Vctora, BC V8W 3P4 CND sourour@mathuvcca bstract We surveys results about somorphsms, Jorda somorphsms,
More informationTHE ROYAL STATISTICAL SOCIETY HIGHER CERTIFICATE
THE ROYAL STATISTICAL SOCIETY 00 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE PAPER I STATISTICAL THEORY The Socety provdes these solutos to assst caddates preparg for the examatos future years ad for the
More informationFundamentals of Regression Analysis
Fdametals of Regresso Aalyss Regresso aalyss s cocered wth the stdy of the depedece of oe varable, the depedet varable, o oe or more other varables, the explaatory varables, wth a vew of estmatg ad/or
More informationSpecial Instructions / Useful Data
JAM 6 Set of all real umbers P A..d. B, p Posso Specal Istructos / Useful Data x,, :,,, x x Probablty of a evet A Idepedetly ad detcally dstrbuted Bomal dstrbuto wth parameters ad p Posso dstrbuto wth
More information( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model
Chapter 3 Asmptotc Theor ad Stochastc Regressors The ature of eplaator varable s assumed to be o-stochastc or fed repeated samples a regresso aalss Such a assumpto s approprate for those epermets whch
More informationLINEAR RECURRENT SEQUENCES AND POWERS OF A SQUARE MATRIX
INTEGERS: ELECTRONIC JOURNAL OF COMBINATORIAL NUMBER THEORY 6 2006, #A12 LINEAR RECURRENT SEQUENCES AND POWERS OF A SQUARE MATRIX Hacèe Belbachr 1 USTHB, Departmet of Mathematcs, POBox 32 El Ala, 16111,
More informationd dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin
Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace
More informationDIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS
DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS Course Project: Classcal Mechacs (PHY 40) Suja Dabholkar (Y430) Sul Yeshwath (Y444). Itroducto Hamltoa mechacs s geometry phase space. It deals
More informationCHAPTER 4 RADICAL EXPRESSIONS
6 CHAPTER RADICAL EXPRESSIONS. The th Root of a Real Number A real umber a s called the th root of a real umber b f Thus, for example: s a square root of sce. s also a square root of sce ( ). s a cube
More informationUnimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods
Malaysa Umodalty Joural Tests of Mathematcal for Global Optmzato Sceces (): of 05 Sgle - 5 Varable (007) Fuctos Usg Statstcal Methods Umodalty Tests for Global Optmzato of Sgle Varable Fuctos Usg Statstcal
More informationApplying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i
CHEMICAL EQUILIBRIA The Thermodyamc Equlbrum Costat Cosder a reversble reacto of the type 1 A 1 + 2 A 2 + W m A m + m+1 A m+1 + Assgg postve values to the stochometrc coeffcets o the rght had sde ad egatve
More informationCan we take the Mysticism Out of the Pearson Coefficient of Linear Correlation?
Ca we tae the Mstcsm Out of the Pearso Coeffcet of Lear Correlato? Itroducto As the ttle of ths tutoral dcates, our purpose s to egeder a clear uderstadg of the Pearso coeffcet of lear correlato studets
More informationMAX-MIN AND MIN-MAX VALUES OF VARIOUS MEASURES OF FUZZY DIVERGENCE
merca Jr of Mathematcs ad Sceces Vol, No,(Jauary 0) Copyrght Md Reader Publcatos wwwjouralshubcom MX-MIN ND MIN-MX VLUES OF VRIOUS MESURES OF FUZZY DIVERGENCE RKTul Departmet of Mathematcs SSM College
More informationExtreme Value Theory: An Introduction
(correcto d Extreme Value Theory: A Itroducto by Laures de Haa ad Aa Ferrera Wth ths webpage the authors ted to form the readers of errors or mstakes foud the book after publcato. We also gve extesos for
More informationStrong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity
BULLETIN of the MALAYSIAN MATHEMATICAL SCIENCES SOCIETY Bull. Malays. Math. Sc. Soc. () 7 (004), 5 35 Strog Covergece of Weghted Averaged Appromats of Asymptotcally Noepasve Mappgs Baach Spaces wthout
More informationIdeal multigrades with trigonometric coefficients
Ideal multgrades wth trgoometrc coeffcets Zarathustra Brady December 13, 010 1 The problem A (, k) multgrade s defed as a par of dstct sets of tegers such that (a 1,..., a ; b 1,..., b ) a j = =1 for all
More informationON THE LOGARITHMIC INTEGRAL
Hacettepe Joural of Mathematcs ad Statstcs Volume 39(3) (21), 393 41 ON THE LOGARITHMIC INTEGRAL Bra Fsher ad Bljaa Jolevska-Tueska Receved 29:9 :29 : Accepted 2 :3 :21 Abstract The logarthmc tegral l(x)
More informationInternational Journal of Mathematical Archive-5(8), 2014, Available online through ISSN
Iteratoal Joural of Mathematcal Archve-5(8) 204 25-29 Avalable ole through www.jma.fo ISSN 2229 5046 COMMON FIXED POINT OF GENERALIZED CONTRACTION MAPPING IN FUZZY METRIC SPACES Hamd Mottagh Golsha* ad
More informationTHE PROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION
Joural of Scece ad Arts Year 12, No. 3(2), pp. 297-32, 212 ORIGINAL AER THE ROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION DOREL MIHET 1, CLAUDIA ZAHARIA 1 Mauscrpt receved: 3.6.212; Accepted
More informationSTATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS. x, where. = y - ˆ " 1
STATISTICAL PROPERTIES OF LEAST SQUARES ESTIMATORS Recall Assumpto E(Y x) η 0 + η x (lear codtoal mea fucto) Data (x, y ), (x 2, y 2 ),, (x, y ) Least squares estmator ˆ E (Y x) ˆ " 0 + ˆ " x, where ˆ
More informationGeneralization of the Dissimilarity Measure of Fuzzy Sets
Iteratoal Mathematcal Forum 2 2007 o. 68 3395-3400 Geeralzato of the Dssmlarty Measure of Fuzzy Sets Faramarz Faghh Boformatcs Laboratory Naobotechology Research Ceter vesa Research Isttute CECR Tehra
More informationPTAS for Bin-Packing
CS 663: Patter Matchg Algorthms Scrbe: Che Jag /9/00. Itroducto PTAS for B-Packg The B-Packg problem s NP-hard. If we use approxmato algorthms, the B-Packg problem could be solved polyomal tme. For example,
More informationChapter 14 Logistic Regression Models
Chapter 4 Logstc Regresso Models I the lear regresso model X β + ε, there are two types of varables explaatory varables X, X,, X k ad study varable y These varables ca be measured o a cotuous scale as
More informationQ-analogue of a Linear Transformation Preserving Log-concavity
Iteratoal Joural of Algebra, Vol. 1, 2007, o. 2, 87-94 Q-aalogue of a Lear Trasformato Preservg Log-cocavty Daozhog Luo Departmet of Mathematcs, Huaqao Uversty Quazhou, Fua 362021, P. R. Cha ldzblue@163.com
More informationOpen and Closed Networks of M/M/m Type Queues (Jackson s Theorem for Open and Closed Networks) Copyright 2015, Sanjay K. Bose 1
Ope ad Closed Networks of //m Type Qees Jackso s Theorem for Ope ad Closed Networks Copyrght 05, Saay. Bose p osso Rate λp osso rocess Average Rate λ p osso Rate λp N p p N osso Rate λp N Splttg a osso
More informationANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK
Far East Joural of Appled Mathematcs Volume, Number, 2008, Pages Ths paper s avalable ole at http://www.pphm.com 2008 Pushpa Publshg House ANALYSIS ON THE NATURE OF THE ASI EQUATIONS IN SYNERGETI INTER-REPRESENTATION
More informationLecture 07: Poles and Zeros
Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto
More informationmeans the first term, a2 means the term, etc. Infinite Sequences: follow the same pattern forever.
9.4 Sequeces ad Seres Pre Calculus 9.4 SEQUENCES AND SERIES Learg Targets:. Wrte the terms of a explctly defed sequece.. Wrte the terms of a recursvely defed sequece. 3. Determe whether a sequece s arthmetc,
More information12.2 Estimating Model parameters Assumptions: ox and y are related according to the simple linear regression model
1. Estmatg Model parameters Assumptos: ox ad y are related accordg to the smple lear regresso model (The lear regresso model s the model that says that x ad y are related a lear fasho, but the observed
More informationAssignment 5/MATH 247/Winter Due: Friday, February 19 in class (!) (answers will be posted right after class)
Assgmet 5/MATH 7/Wter 00 Due: Frday, February 9 class (!) (aswers wll be posted rght after class) As usual, there are peces of text, before the questos [], [], themselves. Recall: For the quadratc form
More informationLecture 3. Sampling, sampling distributions, and parameter estimation
Lecture 3 Samplg, samplg dstrbutos, ad parameter estmato Samplg Defto Populato s defed as the collecto of all the possble observatos of terest. The collecto of observatos we take from the populato s called
More informationN-dimensional Auto-Bäcklund Transformation and Exact Solutions to n-dimensional Burgers System
N-dmesoal Ato-Bäckld Trasformato ad Eact Soltos to -dmesoal Brgers System Mglag Wag Jlag Zhag * & Xagzheg L. School of Mathematcs & Statstcs Hea Uversty of Scece & Techology Loyag 4703 PR Cha. School of
More informationThis article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and
Ths artcle appeared a joral pblshed by Elsever. The attached copy s frshed to the athor for teral o-commercal research ad edcato se, cldg for strcto at the athors sttto ad sharg wth colleages. Other ses,
More informationv 1 -periodic 2-exponents of SU(2 e ) and SU(2 e + 1)
Joural of Pure ad Appled Algebra 216 (2012) 1268 1272 Cotets lsts avalable at ScVerse SceceDrect Joural of Pure ad Appled Algebra joural homepage: www.elsever.com/locate/jpaa v 1 -perodc 2-expoets of SU(2
More information