On computing differential transform of nonlinear non-autonomous functions and its applications

Size: px
Start display at page:

Download "On computing differential transform of nonlinear non-autonomous functions and its applications"

Transcription

1 On compung dfferenal ransform of nonlnear non-auonomous funcons and s applcaons Essam. R. El-Zahar, and Abdelhalm Ebad Deparmen of Mahemacs, Faculy of Scences and Humanes, Prnce Saam Bn Abdulazz Unversy, Alhar, 94, KSA. Deparmen of Basc Engneerng Scence, Faculy of Engneerng, Shebn El-Kom, 5, Menofa Unversy, Egyp. Deparmen of Mahemacs, Faculy of Scence, Tabu Unversy, P. O. Box 74, Tabu 749, KSA Absrac: Alhough beng powerful, he dfferenal ransform mehod ye suffers from a drawbac whch s how o compue he dfferenal ransform of nonlnear non-auonomous funcons ha can lm s applcably. In order o overcome hs defec, we nroduce n hs paper a new general formula and s relaed recurrence relaons for compung he dfferenal ransform of any analyc nonlnear non-auonomous funcon wh one or mul-varable. Regardng, he formula n he leraure was found no applcable o deal wh he presen non-auonomous funcons. Accordngly, a generalzaon s presened n hs paper whch reduces o he correspondng formula n he leraure as a specal case. Several es examples for dfferen ypes of nonlnear dfferenal and negro-dfferenal equaons are solved o demonsrae he valdy and applcably of he presen mehod. The obaned resuls declare ha he suggesed approach no only effecve bu also a sragh forward even n solvng dfferenal and negro-dfferenal equaons wh complex nonlneares. Keywords: Dfferenal ransform mehod; Nonlnear non-auonomous funcons; One-dmensonal dfferenal and negro-dfferenal equaons.. Inroducon The Dfferenal Transform Mehod (DTM) whch s based on Taylor seres expanson was frs nroduced by Zhou [] and has been successfully appled o a wde class of nonlnear problems arsng n mahemacal scences and engneerng. The man advanage of he DTM s ha can be appled drecly o nonlnear dfferenal equaons wh no need for lnearzaon, dscrezaon, or perurbaon. Addonally, he DTM does no generae secular erms (nose erms) and does no need o analycal negraons as oher sem-analycal numercal mehods such as HPM, HAM, ADM or VIM and so he DTM s an aracve ool for solvng dfferenal equaons. Alhough hs mehod has been proved o be an effcen ool for handlng nonlnear dfferenal equaons, he nonlnear funcons used n hese sudes are resrced o ceran nds of nonlneares, e.g., polynomals and producs wh dervaves. For oher ypes of nonlnear funcons, Chang and Chang [] consruc a new algorhm based on obanng a dfferenal equaon sasfed by hs nonlnear funcon and hen applyng he DTM o hs obaned dfferenal equaon. Alhough her reamen was found effecve for some forms of nonlneary [,4] sgnfcanly ncreases he compuaonal budge, especally f here are wo or more nonlnear funcons nvolved n he dfferenal equaon beng nvesgaed, as demonsraed by Ebad [5]. Moreover, n he case of complex nonlneares, may be que dffcul o oban he dfferenal equaons sasfed by hese nonlnear funcons. To overcome hs dffculy, a new formula has been derved [5-8] o calculae

2 he dfferenal ransform of any nonlnear auonomous one varable funcon f ( y ). Ths formula has he same mahemacal srucure as he Adoman polynomals bu wh consans nsead of varable componens. We mean by he nonlnear non-auonomous funcons ha hose nonlnear funcons whch conan he ndependen varable and also he dependen varable and/or s dervaves. Unforunaely, for such ypes of complcaed nonlnear non-auonomous funcons wh one or f, y (), =,,.., m, no relaed formula has been gven o calculae her ransform mul-varable ( ) funcons. Ths provdes he movaon for he presen wor. To overcome he drawbac of he DTM ha s how o compue he dfferenal ransform of hgh complex nonlnear non-auonomous funcons, a generalzed formula s deduced n hs paper for compung he dfferenal ransform of any analyc nonlnear non-auonomous funcon wh one or mul-varable. The proposed mehod deals drecly wh he nonlnear non-auonomous funcon n s form whou any specal nds of ransformaons or algebrac manpulaons. Also, here s no need o compue he dfferenal ransform of oher funcons o oban he requred one. For auonomous funcon, as a specal case of he curren sudy, hese formulas and recurrence relaons have he same mahemacal srucure as he Adoman polynomals bu wh consans nsead of varable componens. The effcency of he proposed mehod s dscussed hrough several es examples ncludng nonlnear dfferenal and negro-dfferenal equaons of dfferen ypes.. Dfferenal Transform Mehod The basc defnons and fundamenal heorems of he one-dmensonal DTM and s applcably for varous nds of dfferenal and negro-dfferenal equaons are gven n [, 9-5]. For convenence of he reader, we presen a bref revew of he DTM n hs secon. The dfferenal ransform of a gven analyc funcon y() n a doman D s defned as d y() Y () =! d =, D, () where y() s he orgnal funcon and Y () s he ransformed funcon. The nverse dfferenal ransform of Y () s defned as. () = y = Y ( ) From Eqs. () and (), we ge d y() y() = ( ) =! d. () = From he above proposon, can be found ha he concep of dfferenal ransform s derved from Taylor seres expanson. In acual applcaons, he funcon y() s expressed by a runcaed seres and Eq. () can be wren as N y = Y ( ), (4) = where N s he approxmaon order of he soluon. Some of he fundamenal mahemacal operaons performed by he one dmensonal dfferenal ransform are lsed n Table.

3 Table. Some fundamenal operaons of he one dmensonal dfferenal ransform. Orgnal funcon y() Transformed funcon Y () β v() ± w () β V ( ) ±β W ( ) v() w () = V () W ( ) m d v() ( + m)! m V + m d! m! ( β+ ) m Hm [, ] ( β+ )!( m )! λ! e λ λ e m, where Hm [, ] =,, f m f m < v( τ) dτ V ( ), V ( ) u () v() τ dτ G(), = m d v ( q ) ( + m)! m m q + V + m d! ω π sn( ω +β ) sn( ω +β+ )! ω π cos( ω +β ) cos( ω +β+ )!. Dfferenal Transform formulas If a dfferenal equaon conans an analyc nonlnear non-auonomous funcon f (, y() ) hen he dfferenal ransform F( n) of he funcon (, ()) he followng heorems, where we assume ha f (, y() ) f f ( y() ). f y s requred and can be compued from Theorem. The dfferenal ransform F( n) of any analyc nonlnear non-auonomous funcon f (, y() ) a a pon can be compued from he formula n d F( n) = f, Y () n +λ λ (4) dλ = λ= where Y () s he dfferenal ransform of y(). Proof: The dfferenal ransform F n of (, ()) f y s defned as n d F( n) = f (, y() n ) d =. (5) Subsung Eq. n Eq.5 resuls n

4 n d F( n) = f, Y ( ) n d. (6) = = Now, le =λ, hen Eq.6 becomes n d F( n) = f, Y () n +λ λ. dλ = λ= By hs way, he proof of Theorem s compleed. Theorem. The dfferenal ransform F( n) of any analyc nonlnear non-auonomous funcon f (, y() ) a a pon, sasfes he recurrence relaon where F() f (, Y ()) n F( n) = F( n ) + ( + ) Y F( n ), n =,,.., n = Y () (7) =. Proof: we have f n (, y()) f n (, y() ) f n (, y() ) dy = + y () d (), hen F( n) = f, Y ( ) + f, Y ( ) ( + ) Y ( + ) Y () ( n ) ( n ) = = = = = ( n )! F ( n ) + ( n )! ( + ) Y ( ) F ( n ) = Y () and snce F( n ) s a funcon of and { ()} n Y, hen = n F( n) = F( n ) + ( + ) Y F( n ) n = Y () By hs way, he proof of Theorem s compleed. Thus by Theorems and we have mplemened a new algorhm for compung he one-dmensonal dfferenal ransform of any analyc nonlnear funcon non-auonomous f y. (, ()) We observe ha for auonomous funcon, he defnon (4) and recurrence relaon (7) are reduced o, respecvely n d F( n) = f Y () n λ, (8) dλ = λ= n F( n) = ( + ) Y ( ) F( n ), n =,,... (9) n = Y ( ) One can observe ha he resul n (8) s he presen formula n [5-8] 4

5 In fac f a sysem of one-dmensonal dfferenal equaons conans a coupled analyc f, y (),,,.., m f, y () f f y () f y ()... f y () nonlneary ( ) =, where we assume ha m m, hen Theorems and can be easly exended usng he above presen procedure o mul-varable funcon and sasfy he followng recurrence algorhms Corollary. The dfferenal ransform F n of any analyc non-auonomous funcon (, ()) f y, =,,.., m a a pon can be defned by n d F( n) = f, Y () n +λ λ dλ, =,,.., m () where Y () s he dfferenal ransform of y (). = λ= Corollary. The dfferenal ransform =,,.., m a a pon, sasfes he recurrence relaon F n of any analyc non-auonomous funcon (, ()) f y, m n F( n) = F( n ) + ( + ) Y ( ) F( n ), n =,,.., n = = Y ( ) () where F() f (, Y ()) =. Moreover for auonomous funcon, he defnon () and recurrence relaon () are reduced, respecvely, o n d F( n) = f Y () n λ, =,,.., m, () dλ = λ= m n F( n) = ( + ) Y ( ) F( n ), =,,.., m, n =,,.., n () = = Y ( ) whch have he same mahemacal srucure as he Adoman polynomals [6] bu wh consans nsead of varable componens. 4. Resuls In hs secon, we have solved dfferen ypes of dfferenal and negro-dfferenal problems wh dfferen forms of nonlnear non-auonomous funcons o demonsrae he valdy and applcably of he presen mehod. Example. Consder he nonlnear nal-value problem y () y() = ln + y(), () y =. (۱٤) Usng he basc properes of DTM and ang he ransform of equaons n (4) resul n 5

6 ( + ) Y ( + ) Y ( ) = F( ), Y () =, =,,,..., (5) where F( ) s he dfferenal ransform of he nonlnear erm ln( + y). F( ) s compued usng he presen mehod and gven by ( Y ), Y () ( + Y () ), Y ( + Y ()) ( )) ( Y )) 4 Y ( Y )) 4( Y ()) + Y () F() = ln( + Y ()), F() = F() = + Y () + () Y () Y () + Y () + Y ( F () = +, + Y () + () + ( Y (4) Y () + Y () Y () + Y () () + Y () F (4) = + + Y () + Y () + Y () + ( + 4 Therefore, a combnaon of (5) and (6) resuls n he seres soluon. (6) y = For suffcenly large number of erms, he closed form of he soluon s y() e =, whch s he exac soluon. Table shows he absolue error obaned for hree varous numbers of erms and a some es pons. Table : Numercal resuls for Example. y y N = 5 N = N = e-8 6.e e e-6.869e- 4.6e e e- 5.55e e-4.48e e-5..65e-.7e-8 5.8e-4 Example. Consder he nonlnear nal-value problem y () + εy() = εsn( y()), y () =. (7) Tang he dfferenal ransform of equaons n (7) resuls n ( + ) Y ( + ) + ε Y Y ( ) Y ( ) = εf( ), Y () =, =,,,..., (8) = where F( ) s he dfferenal ransform of he nonlnear erm sn( y ( )). F( ) usng he presen mehod and gven by s compued 6

7 Y () F() =, F() = Y (), F() = Y (), F() = + Y (), 6 5 F(4) = y() Y () y(), F(5) = Y Y () Y () Y () Y + Y (4) Usng (8) and (9), he seres soluon s obaned and gven a ε =. by. (9) y = The presened resuls are compared wh hose obaned usng MATLAB bul-n solver ode45 n Table. The ode45 solver negraes ODEs usng explc 4h & 5h Runge-Kua (4, 5) formula [7]. In order o guaranee a good numercal reference, ode45 s confgured usng an absolue error of 8 and relave error of. Table : Numercal resuls for Example. y( ) y ( ) N = 5 N = N = e-6 8.e- 9.66e e-4.79e-6.9e e-.5e-4.e e-.4e-.654e e-.556e- 8.8e- Example. Consder he followng nonlnear problem wh mulple soluons ( ) y () y() + = +, () y =. () The dfferenal ransform of equaons n () are = + () ( + ) Y ( + ) H(, ) = F( ) ( )! ( + )! and Y () =, where F( ) s he dfferenal ransform of he nonlnear erm + y(). Applyng he presen mehod o he nonlnear funcon f (, y()) = + y() a = and Y () =,resuls n Y () F() =±, F() =±, F() =± +, F() =± Y () + Y () Y () F(4) =± Y () + Y () + ( 8 Y () 64 Y ()) Y () + Y (), () 4 Y () Y () Y () 5 Y () Y () Y () 7 Y () F(5) =± + Y (4) + Y () + + Y () Y () where he braces wh posve sgn are due o usng he prncpal square roos whle he braces wh negave sgn are due o usng he negave roos. Therefore, a combnaon of () and () resuls n wo seres soluon gven by 7

8 y () =±, whch are he exac soluons of (). Example 4. Consder he nonlnear frs order Volerra negro-dfferenal equaon y = cos + + sn ( + y) d τ τ τ, y =, y =. () The dfferenal ransform of equaons n () are π δ( ) F( ) ( + ) Y ( + ) = cos +δ ( ) +, Y () =, Y () =,!, where F( ) s he dfferenal ransform of he nonlnear erm sn ( τ + y ( τ )). By applyng he presen mehod o he nonlnear funcon f ( τ, y( τ)) = sn ( τ + y( τ )) a τ =, Y () = and Y () =, and by usng he prncpal value of he square roo and nverse rgonomerc funcons, we ge F() =, F() =, F() = Y (), F() = Y () +, F(4) = Y (4) + Y (), 6 F(5) Y (5) Y () Y (), F(6) Y () Y (4) Y () Y () Y (6) Y () = = F(7) 56 Y () 84 Y () Y () Y (4) Y () Y (5) Y (7) Y () = Hence, he seres soluon s obaned and gven by. () y = For suffcenly large number of erms, he closed form of he soluon s y = sn +, whch s he exac soluon. Table 4 shows he absolue error obaned for hree varous numbers of erms and a some es pons. Table 4: Numercal resuls for Example 4. y( ) y ( ) N = 5 N = N = e e-6.e e-7.497e- 5.55e e e-.e e-5.4e-9.e e-4.489e e-5 Example 5. Consder he nonlnear second order Volerra negro-dfferenal equaon 8

9 sec τ y () y() y () = + dτ + y ( τ ), y () =, y () =. (4) The dfferenal ransform of equaons n (4) are F( ) ( + )( + ) Y ( + ) = ( + ) Y ( + ) Y ( ) δ( ) +, Y () =, Y () =, Y () =, = sec τ,where F( ) s he dfferenal ransform of he nonlnear erm obaned usng he presen + y ( τ ) mehod a τ = and gven by F() =, F() =, F() =, F() =, F(4) = Y (), Y (5) = Y (4), F(6) = Y (5) + Y () Y (), F(6) = ( Y ()) Y (4) Y (6), 45 7 F(7) 5 Y () Y () Y () Y (5) Y (5) Y (7) Y (4) = Hence, he approxmae seres soluon s obaned and gven by (5) 7 6 y = For suffcenly large number of erms, he closed form of he soluon s y = an, whch s he exac soluon. Table 5 shows he absolue error obaned for hree varous numbers of erms and a some es pons. Table 5: Numercal resuls for Example 5. y( ) y ( ) N = 5 N = N = e-7.845e- 8.49e e-5.975e-7.89e e-.7649e-5.69e e-.8e-.799e e-.49e- 9.9e-4 Example 6. Consder he nonlnear Volerra negro-dfferenal equaon wh proporonal delay ( τ ) y sn y = sn + d τ (τ + ) The dfferenal ransform of equaons n (6) are, y () =, y () =. (6) + F π π ( ) ( + ) Y ( + ) = δ( ) sn δ( ) + sn, Y () =, Y () =,,!! = = 9

10 where F( ) s he dfferenal ransform of he nonlnear erm w τ, w ( τ) = Y ( ) τ (τ + ) obaned usng he presen mehod and gven by = F() =, F() =, F() = 8 Y (), F() = 54 Y () + 54 Y (), F(4) = 8 Y () + 6 Y () 6 Y () + 6 Y (4), F(5) = 486 Y () + (486 Y () 486) Y () 486 Y (4) Y (5) Y () Hence, he seres soluon s obaned and gven by. (7) y () = +, whch s he exac soluon. Example 7. Consder he followng nonlnear non-auonomous nal-value ODE sysem y () = y() + + ln y() + y () 4 y () = y () + ln ( + y () ). (8) y() y() =, y () = Applyng he dfferenal ransform o (8), resuls n + + =δ + ( ) Y ( ) ( K ) Y ( ) F( ) ( + ) Y ( + ) = Y ( ) δ ( K) + F ( ). (9) Y () =, Y () = where F( ) and F are he dfferenal ransform of he nonlnear funcons 4 f = ln y and f = ln ( + y ) + y () y(), respecvely. F ( ) and F ( are compued usng formula() and gven by F() =, F() = Y () + + Y (), F() = Y () ( + Y () ) + Y () ( Y () + + Y () ) F() = Y () + ( + Y () ) ( + Y () ) Y () + Y (), ( Y () Y () Y () + Y () )( Y () + + Y () ) + ( Y () + + Y () ) () F() =, F() = Y () Y () F() = Y () Y () Y () + ( + Y () ), F() = Y () + Y () Y () Y () Y () + ( + Y () ) Y () ( + Y () ) 4 () Hence, he seres soluons are obaned and gven as y =

11 y = For suffcenly large number of erms, he closed forms of he soluons are () y = e, y () = e, whch are he exac soluons. Table 6 shows he absolue error obaned for hree varous numbers of erms and a some es pons. Table 6: Numercal resuls for Example 7 y y y y N = 5 N = N = 5 N = 5 N = N = e-7.e-5.5e e e-6.4e e-5.e e-6 6.e-6.87e-.4e e-4.79e-.4e-6 7.8e e- ٤ ٥۱۰۱e e-4 4.7e-9.555e-5 4.6e-4.48e e e- 4.69e-8 9.9e-4.65e-.7e e-4 Tables 5 show he absolue errors of he presen mehod for dfferen approxmaon order, N, of he soluon and a some es pons. The resuls show ha he obaned soluons are accurae and converge o he exac ones wh ncreasng he order N. 5. Conclusons In hs paper, a new general formula and hence new recurrence relaons have been derved for compung he dfferenal ransform of any analyc nonlnear non-auonomous funcons wh one or mul-varable. As a specal case of he presen sudy,.e., for auonomous funcon, he curren formulas and recurrence relaons reduces o he same mahemacal srucure as he Adoman polynomals bu wh consans nsead of varable componens n he leraure. I was found ha, he suggesed mehod deals drecly wh he nonlnear non-auonomous funcons, where specal ransformaon or algebrac manpulaons were compleely avoded. In addon, he mehod has been successfully appled on dfferen ypes of dfferenal and nego-dfferenal equaons. Moreover, he obaned seres soluons demonsrae he valdy and applcably of he presen approach. Numercally, he resuls showed ha a fas convergence has been acheved for he obaned seres soluons. An advanage of he presen mehod s ha can be combned wh Padé Approxman (PA), Aferreamen Technques (AT), Power Seres Exender Mehod (PSEM) and mul-sep echnque, among many ohers. Fnally, he auhors beleve ha he presen sudy should be exended o nclude smlar dfferenal and nego-dfferenal equaons n he appled scences, whch ncreases s applcably. Conflcs of Ineres: Auhor has declared ha no compeng neress exs. References. Zhou, J. K., 986. Dfferenal Transformaon and s Applcaons for Elecrcal Crcus, Huazhong Unversy Press, Wuhan Chna 986. Chang, S. H., & Chang, I. L. (8). A new algorhm for calculang one-dmensonal dfferenal ransform of nonlnear funcons. Appled Mahemacs and Compuaon, 95(),

12 . Ebad, A. (). Approxmae perodc soluons for he non-lnear relavsc harmonc oscllaor va dfferenal ransformaon mehod. Communcaons n Nonlnear Scence and Numercal Smulaon, 5(7), Ebad, A. (). A relable aferreamen for mprovng he dfferenal ransformaon mehod and s applcaon o nonlnear oscllaors wh fraconal nonlneares. Communcaons n Nonlnear Scence and Numercal Smulaon, 6(), Ebad, A. (). On a new dfferenal ransformaon mehod for solvng nonlnear dfferenal equaons. Asan-European Journal of Mahemacs, 6(4), Behry, S. H. (). Dfferenal Transform Mehod for Nonlnear Inal-Value Problems by Adoman Polynomals. Journal of Appled & Compuaonal Mahemacs,. 7. N, H. S., & Soleyman, F. (). A Taylor-ype numercal mehod for solvng nonlnear ordnary dfferenal equaons. Alexandra Engneerng Journal, 5(), Faoorehch, H., & Abolghasem, H. (). Improvng he dfferenal ransform mehod: a novel echnque o oban he dfferenal ransforms of nonlneares by he Adoman polynomals. Appled Mahemacal Modellng, 7(8), Odba, Z. M. (8). Dfferenal ransform mehod for solvng Volerra negral equaon wh separable ernels. Mahemacal and Compuer Modellng, 48(7), Abdulaw, M. (5). Soluon of Cauchy ype sngular negral equaons of he frs nd by usng dfferenal ransform mehod. Appled Mahemacal Modellng, 9(8), EL-Zahar, E. R. (). Approxmae analycal soluons of sngularly perurbed fourh order boundary value problems usng dfferenal ransform mehod, Journal of Kng Saud Unversy (Scence), 5(), El-Zahar, E. R. (5). Applcaons of Adapve Mul sep Dfferenal Transform Mehod o Sngular Perurbaon Problems Arsng n Scence and Engneerng, Appled Mahemacs and Informaon Scences, 9(), -.. El-Zahar, E. R. (6). Pecewse approxmae analycal soluons of hgh order sngular perurbaon problems wh a dsconnuous source erm, Inernaonal Journal of Dfferenal Equaons, vol. 6, Arcle ID 564, pages, 6. do:.55/6/ Erür, V. S., Odba, Z. M., & Moman, S. (). The mul-sep dfferenal ransform mehod and s applcaon o deermne he soluons of non-lnear oscllaors. Advances n Appled Mahemacs and Mechancs, 4(4), Aroglu, A., & Ozol, I. (8). Soluons of negral and negro-dfferenal equaon sysems by usng dfferenal ransform mehod. Compuers & Mahemacs wh Applcaons, 56(9), Duan, J. S. (). Convenen analyc recurrence algorhms for he Adoman polynomals. Appled Mahemacs and Compuaon, 7(), Dormand, J. R., & Prnce, P. J. (98). A famly of embedded Runge-Kua formulae. Journal of compuaonal and appled mahemacs, 6(), 9-6.

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae

More information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,

More information

A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION

A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION S19 A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION by Xaojun YANG a,b, Yugu YANG a*, Carlo CATTANI c, and Mngzheng ZHU b a Sae Key Laboraory for Geomechancs and Deep Underground Engneerng, Chna Unversy

More information

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran

More information

On One Analytic Method of. Constructing Program Controls

On One Analytic Method of. Constructing Program Controls Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna

More information

Cubic Bezier Homotopy Function for Solving Exponential Equations

Cubic Bezier Homotopy Function for Solving Exponential Equations Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.

More information

M. Y. Adamu Mathematical Sciences Programme, AbubakarTafawaBalewa University, Bauchi, Nigeria

M. Y. Adamu Mathematical Sciences Programme, AbubakarTafawaBalewa University, Bauchi, Nigeria IOSR Journal of Mahemacs (IOSR-JM e-issn: 78-578, p-issn: 9-765X. Volume 0, Issue 4 Ver. IV (Jul-Aug. 04, PP 40-44 Mulple SolonSoluons for a (+-dmensonalhroa-sasuma shallow waer wave equaon UsngPanlevé-Bӓclund

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 0 Canoncal Transformaons (Chaper 9) Wha We Dd Las Tme Hamlon s Prncple n he Hamlonan formalsm Dervaon was smple δi δ Addonal end-pon consrans pq H( q, p, ) d 0 δ q ( ) δq ( ) δ

More information

Relative controllability of nonlinear systems with delays in control

Relative controllability of nonlinear systems with delays in control Relave conrollably o nonlnear sysems wh delays n conrol Jerzy Klamka Insue o Conrol Engneerng, Slesan Techncal Unversy, 44- Glwce, Poland. phone/ax : 48 32 37227, {jklamka}@a.polsl.glwce.pl Keywor: Conrollably.

More information

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation Global Journal of Pure and Appled Mahemacs. ISSN 973-768 Volume 4, Number 6 (8), pp. 89-87 Research Inda Publcaons hp://www.rpublcaon.com Exsence and Unqueness Resuls for Random Impulsve Inegro-Dfferenal

More information

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon

More information

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal

More information

Chapter Lagrangian Interpolation

Chapter Lagrangian Interpolation Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and

More information

Including the ordinary differential of distance with time as velocity makes a system of ordinary differential equations.

Including the ordinary differential of distance with time as velocity makes a system of ordinary differential equations. Soluons o Ordnary Derenal Equaons An ordnary derenal equaon has only one ndependen varable. A sysem o ordnary derenal equaons consss o several derenal equaons each wh he same ndependen varable. An eample

More information

A DECOMPOSITION METHOD FOR SOLVING DIFFUSION EQUATIONS VIA LOCAL FRACTIONAL TIME DERIVATIVE

A DECOMPOSITION METHOD FOR SOLVING DIFFUSION EQUATIONS VIA LOCAL FRACTIONAL TIME DERIVATIVE S13 A DECOMPOSITION METHOD FOR SOLVING DIFFUSION EQUATIONS VIA LOCAL FRACTIONAL TIME DERIVATIVE by Hossen JAFARI a,b, Haleh TAJADODI c, and Sarah Jane JOHNSTON a a Deparen of Maheacal Scences, Unversy

More information

P R = P 0. The system is shown on the next figure:

P R = P 0. The system is shown on the next figure: TPG460 Reservor Smulaon 08 page of INTRODUCTION TO RESERVOIR SIMULATION Analycal and numercal soluons of smple one-dmensonal, one-phase flow equaons As an nroducon o reservor smulaon, we wll revew he smples

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure

More information

( ) () we define the interaction representation by the unitary transformation () = ()

( ) () we define the interaction representation by the unitary transformation () = () Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger

More information

FTCS Solution to the Heat Equation

FTCS Solution to the Heat Equation FTCS Soluon o he Hea Equaon ME 448/548 Noes Gerald Reckenwald Porland Sae Unversy Deparmen of Mechancal Engneerng gerry@pdxedu ME 448/548: FTCS Soluon o he Hea Equaon Overvew Use he forward fne d erence

More information

Method of upper lower solutions for nonlinear system of fractional differential equations and applications

Method of upper lower solutions for nonlinear system of fractional differential equations and applications Malaya Journal of Maemak, Vol. 6, No. 3, 467-472, 218 hps://do.org/1.26637/mjm63/1 Mehod of upper lower soluons for nonlnear sysem of fraconal dfferenal equaons and applcaons D.B. Dhagude1 *, N.B. Jadhav2

More information

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5 TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres

More information

Tight results for Next Fit and Worst Fit with resource augmentation

Tight results for Next Fit and Worst Fit with resource augmentation Tgh resuls for Nex F and Wors F wh resource augmenaon Joan Boyar Leah Epsen Asaf Levn Asrac I s well known ha he wo smple algorhms for he classc n packng prolem, NF and WF oh have an approxmaon rao of

More information

Research Article Numerical Approximation of Higher-Order Solutions of the Quadratic Nonlinear Stochastic Oscillatory Equation Using WHEP Technique

Research Article Numerical Approximation of Higher-Order Solutions of the Quadratic Nonlinear Stochastic Oscillatory Equation Using WHEP Technique Hndaw Publshng Corporaon Journal of Appled Mahemacs Volume 3, Arcle ID 68537, pages hp://dx.do.org/.55/3/68537 Research Arcle Numercal Approxmaon of Hgher-Order Soluons of he Quadrac Nonlnear Sochasc Oscllaory

More information

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas)

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas) Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on

More information

New M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study)

New M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study) Inernaonal Mahemacal Forum, Vol. 8, 3, no., 7 - HIKARI Ld, www.m-hkar.com hp://dx.do.org/.988/mf.3.3488 New M-Esmaor Objecve Funcon n Smulaneous Equaons Model (A Comparave Sudy) Ahmed H. Youssef Professor

More information

Survival Analysis and Reliability. A Note on the Mean Residual Life Function of a Parallel System

Survival Analysis and Reliability. A Note on the Mean Residual Life Function of a Parallel System Communcaons n Sascs Theory and Mehods, 34: 475 484, 2005 Copyrgh Taylor & Francs, Inc. ISSN: 0361-0926 prn/1532-415x onlne DOI: 10.1081/STA-200047430 Survval Analyss and Relably A Noe on he Mean Resdual

More information

FI 3103 Quantum Physics

FI 3103 Quantum Physics /9/4 FI 33 Quanum Physcs Aleander A. Iskandar Physcs of Magnesm and Phooncs Research Grou Insu Teknolog Bandung Basc Conces n Quanum Physcs Probably and Eecaon Value Hesenberg Uncerany Prncle Wave Funcon

More information

On the numerical treatment ofthenonlinear partial differentialequation of fractional order

On the numerical treatment ofthenonlinear partial differentialequation of fractional order IOSR Journal of Mahemacs (IOSR-JM) e-iss: 2278-5728, p-iss: 239-765X. Volume 2, Issue 6 Ver. I (ov. - Dec.26), PP 28-37 www.osrjournals.org On he numercal reamen ofhenonlnear paral dfferenalequaon of fraconal

More information

Handout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system Y X (2) and write EOM (1) as two first-order Eqs.

Handout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system Y X (2) and write EOM (1) as two first-order Eqs. Handou # 6 (MEEN 67) Numercal Inegraon o Fnd Tme Response of SDOF mechancal sysem Sae Space Mehod The EOM for a lnear sysem s M X DX K X F() () X X X X V wh nal condons, a 0 0 ; 0 Defne he followng varables,

More information

In the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!") i+1,q - [(!

In the complete model, these slopes are ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL. (! i+1 -! i ) + [(!) i+1,q - [(! ANALYSIS OF VARIANCE FOR THE COMPLETE TWO-WAY MODEL The frs hng o es n wo-way ANOVA: Is here neracon? "No neracon" means: The man effecs model would f. Ths n urn means: In he neracon plo (wh A on he horzonal

More information

3. OVERVIEW OF NUMERICAL METHODS

3. OVERVIEW OF NUMERICAL METHODS 3 OVERVIEW OF NUMERICAL METHODS 3 Inroducory remarks Ths chaper summarzes hose numercal echnques whose knowledge s ndspensable for he undersandng of he dfferen dscree elemen mehods: he Newon-Raphson-mehod,

More information

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair TECHNI Inernaonal Journal of Compung Scence Communcaon Technologes VOL.5 NO. July 22 (ISSN 974-3375 erformance nalyss for a Nework havng Sby edundan Un wh ang n epar Jendra Sngh 2 abns orwal 2 Deparmen

More information

Attribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b

Attribute Reduction Algorithm Based on Discernibility Matrix with Algebraic Method GAO Jing1,a, Ma Hui1, Han Zhidong2,b Inernaonal Indusral Informacs and Compuer Engneerng Conference (IIICEC 05) Arbue educon Algorhm Based on Dscernbly Marx wh Algebrac Mehod GAO Jng,a, Ma Hu, Han Zhdong,b Informaon School, Capal Unversy

More information

NATIONAL UNIVERSITY OF SINGAPORE PC5202 ADVANCED STATISTICAL MECHANICS. (Semester II: AY ) Time Allowed: 2 Hours

NATIONAL UNIVERSITY OF SINGAPORE PC5202 ADVANCED STATISTICAL MECHANICS. (Semester II: AY ) Time Allowed: 2 Hours NATONAL UNVERSTY OF SNGAPORE PC5 ADVANCED STATSTCAL MECHANCS (Semeser : AY 1-13) Tme Allowed: Hours NSTRUCTONS TO CANDDATES 1. Ths examnaon paper conans 5 quesons and comprses 4 prned pages.. Answer all

More information

Solution in semi infinite diffusion couples (error function analysis)

Solution in semi infinite diffusion couples (error function analysis) Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of

More information

Chapter 6: AC Circuits

Chapter 6: AC Circuits Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.

More information

Solving the multi-period fixed cost transportation problem using LINGO solver

Solving the multi-period fixed cost transportation problem using LINGO solver Inernaonal Journal of Pure and Appled Mahemacs Volume 119 No. 12 2018, 2151-2157 ISSN: 1314-3395 (on-lne verson) url: hp://www.pam.eu Specal Issue pam.eu Solvng he mul-perod fxed cos ransporaon problem

More information

Notes on the stability of dynamic systems and the use of Eigen Values.

Notes on the stability of dynamic systems and the use of Eigen Values. Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon

More information

Implementation of Quantized State Systems in MATLAB/Simulink

Implementation of Quantized State Systems in MATLAB/Simulink SNE T ECHNICAL N OTE Implemenaon of Quanzed Sae Sysems n MATLAB/Smulnk Parck Grabher, Mahas Rößler 2*, Bernhard Henzl 3 Ins. of Analyss and Scenfc Compung, Venna Unversy of Technology, Wedner Haupsraße

More information

FRACTIONAL OPTICAL SOLITARY WAVE SOLUTIONS OF THE HIGHER-ORDER NONLINEAR SCHRÖDINGER EQUATION

FRACTIONAL OPTICAL SOLITARY WAVE SOLUTIONS OF THE HIGHER-ORDER NONLINEAR SCHRÖDINGER EQUATION THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY Seres A OF THE ROMANIAN ACADEMY Volume Number /00x pp. 9 00 FRACTIONAL OPTICAL SOLITARY WAVE SOLUTIONS OF THE HIGHER-ORDER NONLINEAR SCHRÖDINGER

More information

The Finite Element Method for the Analysis of Non-Linear and Dynamic Systems

The Finite Element Method for the Analysis of Non-Linear and Dynamic Systems Swss Federal Insue of Page 1 The Fne Elemen Mehod for he Analyss of Non-Lnear and Dynamc Sysems Prof. Dr. Mchael Havbro Faber Dr. Nebojsa Mojslovc Swss Federal Insue of ETH Zurch, Swzerland Mehod of Fne

More information

Delay-Range-Dependent Stability Analysis for Continuous Linear System with Interval Delay

Delay-Range-Dependent Stability Analysis for Continuous Linear System with Interval Delay Inernaonal Journal of Emergng Engneerng esearch an echnology Volume 3, Issue 8, Augus 05, PP 70-76 ISSN 349-4395 (Prn) & ISSN 349-4409 (Onlne) Delay-ange-Depenen Sably Analyss for Connuous Lnear Sysem

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4 CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped

More information

PHYS 705: Classical Mechanics. Canonical Transformation

PHYS 705: Classical Mechanics. Canonical Transformation PHYS 705: Classcal Mechancs Canoncal Transformaon Canoncal Varables and Hamlonan Formalsm As we have seen, n he Hamlonan Formulaon of Mechancs,, are ndeenden varables n hase sace on eual foong The Hamlon

More information

e-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov

e-journal Reliability: Theory& Applications No 2 (Vol.2) Vyacheslav Abramov June 7 e-ournal Relably: Theory& Applcaons No (Vol. CONFIDENCE INTERVALS ASSOCIATED WITH PERFORMANCE ANALYSIS OF SYMMETRIC LARGE CLOSED CLIENT/SERVER COMPUTER NETWORKS Absrac Vyacheslav Abramov School

More information

How about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?

How about the more general linear scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )? lmcd Lnear ransformaon of a vecor he deas presened here are que general hey go beyond he radonal mar-vecor ype seen n lnear algebra Furhermore, hey do no deal wh bass and are equally vald for any se of

More information

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class

More information

Volatility Interpolation

Volatility Interpolation Volaly Inerpolaon Prelmnary Verson March 00 Jesper Andreasen and Bran Huge Danse Mares, Copenhagen wan.daddy@danseban.com brno@danseban.com Elecronc copy avalable a: hp://ssrn.com/absrac=69497 Inro Local

More information

First-order piecewise-linear dynamic circuits

First-order piecewise-linear dynamic circuits Frs-order pecewse-lnear dynamc crcus. Fndng he soluon We wll sudy rs-order dynamc crcus composed o a nonlnear resse one-por, ermnaed eher by a lnear capacor or a lnear nducor (see Fg.. Nonlnear resse one-por

More information

Mohammad H. Al-Towaiq a & Hasan K. Al-Bzoor a a Department of Mathematics and Statistics, Jordan University of

Mohammad H. Al-Towaiq a & Hasan K. Al-Bzoor a a Department of Mathematics and Statistics, Jordan University of Ths arcle was downloaded by: [Jordan Unv. of Scence & Tech] On: 05 Aprl 05, A: 0:4 Publsher: Taylor & Francs Informa Ld Regsered n England and ales Regsered umber: 07954 Regsered offce: Mormer House, 37-4

More information

Bayesian Inference of the GARCH model with Rational Errors

Bayesian Inference of the GARCH model with Rational Errors 0 Inernaonal Conference on Economcs, Busness and Markeng Managemen IPEDR vol.9 (0) (0) IACSIT Press, Sngapore Bayesan Inference of he GARCH model wh Raonal Errors Tesuya Takash + and Tng Tng Chen Hroshma

More information

Generalized double sinh-gordon equation: Symmetry reductions, exact solutions and conservation laws

Generalized double sinh-gordon equation: Symmetry reductions, exact solutions and conservation laws IJS (05) 9A: 89-96 Iranan Journal of Scence & echnology hp://ss.shrazu.ac.r Generalzed double snh-gordon equaon: Symmery reducons eac soluons and conservaon laws G. Magalawe B. Muaeea and C. M. Khalque

More information

Robust and Accurate Cancer Classification with Gene Expression Profiling

Robust and Accurate Cancer Classification with Gene Expression Profiling Robus and Accurae Cancer Classfcaon wh Gene Expresson Proflng (Compuaonal ysems Bology, 2005) Auhor: Hafeng L, Keshu Zhang, ao Jang Oulne Background LDA (lnear dscrmnan analyss) and small sample sze problem

More information

Coupled Method for Solving Time-Fractional Navier-Stokes Equation

Coupled Method for Solving Time-Fractional Navier-Stokes Equation INTERNATIONAL JOURNAL OF CIRCUITS, SYSTEMS AND SIGNAL PROCESSING Volume, 8 Coupled Mehod for Solng Tme-Fraconal Naer-Sokes Equaon S. O. Edek, and G. O. Aknlab Absrac Ths paper wnesses he couplng of wo

More information

Comparison of Differences between Power Means 1

Comparison of Differences between Power Means 1 In. Journal of Mah. Analyss, Vol. 7, 203, no., 5-55 Comparson of Dfferences beween Power Means Chang-An Tan, Guanghua Sh and Fe Zuo College of Mahemacs and Informaon Scence Henan Normal Unversy, 453007,

More information

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes. umercal negraon of he dffuson equaon (I) Fne dfference mehod. Spaal screaon. Inernal nodes. R L V For hermal conducon le s dscree he spaal doman no small fne spans, =,,: Balance of parcles for an nernal

More information

Supplementary Material to: IMU Preintegration on Manifold for E cient Visual-Inertial Maximum-a-Posteriori Estimation

Supplementary Material to: IMU Preintegration on Manifold for E cient Visual-Inertial Maximum-a-Posteriori Estimation Supplemenary Maeral o: IMU Prenegraon on Manfold for E cen Vsual-Ineral Maxmum-a-Poseror Esmaon echncal Repor G-IRIM-CP&R-05-00 Chrsan Forser, Luca Carlone, Fran Dellaer, and Davde Scaramuzza May 0, 05

More information

A New Generalized Gronwall-Bellman Type Inequality

A New Generalized Gronwall-Bellman Type Inequality 22 Inernaonal Conference on Image, Vson and Comung (ICIVC 22) IPCSIT vol. 5 (22) (22) IACSIT Press, Sngaore DOI:.7763/IPCSIT.22.V5.46 A New Generalzed Gronwall-Bellman Tye Ineualy Qnghua Feng School of

More information

Let s treat the problem of the response of a system to an applied external force. Again,

Let s treat the problem of the response of a system to an applied external force. Again, Page 33 QUANTUM LNEAR RESPONSE FUNCTON Le s rea he problem of he response of a sysem o an appled exernal force. Agan, H() H f () A H + V () Exernal agen acng on nernal varable Hamlonan for equlbrum sysem

More information

Department of Economics University of Toronto

Department of Economics University of Toronto Deparmen of Economcs Unversy of Torono ECO408F M.A. Economercs Lecure Noes on Heeroskedascy Heeroskedascy o Ths lecure nvolves lookng a modfcaons we need o make o deal wh he regresson model when some of

More information

2/20/2013. EE 101 Midterm 2 Review

2/20/2013. EE 101 Midterm 2 Review //3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance

More information

@FMI c Kyung Moon Sa Co.

@FMI c Kyung Moon Sa Co. Annals of Fuzzy Mahemacs and Informacs Volume 8, No. 2, (Augus 2014), pp. 245 257 ISSN: 2093 9310 (prn verson) ISSN: 2287 6235 (elecronc verson) hp://www.afm.or.kr @FMI c Kyung Moon Sa Co. hp://www.kyungmoon.com

More information

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng

More information

Sampling Procedure of the Sum of two Binary Markov Process Realizations

Sampling Procedure of the Sum of two Binary Markov Process Realizations Samplng Procedure of he Sum of wo Bnary Markov Process Realzaons YURY GORITSKIY Dep. of Mahemacal Modelng of Moscow Power Insue (Techncal Unversy), Moscow, RUSSIA, E-mal: gorsky@yandex.ru VLADIMIR KAZAKOV

More information

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he

More information

Time-interval analysis of β decay. V. Horvat and J. C. Hardy

Time-interval analysis of β decay. V. Horvat and J. C. Hardy Tme-nerval analyss of β decay V. Horva and J. C. Hardy Work on he even analyss of β decay [1] connued and resuled n he developmen of a novel mehod of bea-decay me-nerval analyss ha produces hghly accurae

More information

DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL

DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL DEEP UNFOLDING FOR MULTICHANNEL SOURCE SEPARATION SUPPLEMENTARY MATERIAL Sco Wsdom, John Hershey 2, Jonahan Le Roux 2, and Shnj Waanabe 2 Deparmen o Elecrcal Engneerng, Unversy o Washngon, Seale, WA, USA

More information

Lecture 11 SVM cont

Lecture 11 SVM cont Lecure SVM con. 0 008 Wha we have done so far We have esalshed ha we wan o fnd a lnear decson oundary whose margn s he larges We know how o measure he margn of a lnear decson oundary Tha s: he mnmum geomerc

More information

10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current :

10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current : . A. IUITS Synopss : GOWTH OF UNT IN IUIT : d. When swch S s closed a =; = d. A me, curren = e 3. The consan / has dmensons of me and s called he nducve me consan ( τ ) of he crcu. 4. = τ; =.63, n one

More information

Robustness Experiments with Two Variance Components

Robustness Experiments with Two Variance Components Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference

More information

Fuzzy Set Theory in Modeling Uncertainty Data. via Interpolation Rational Bezier Surface Function

Fuzzy Set Theory in Modeling Uncertainty Data. via Interpolation Rational Bezier Surface Function Appled Mahemacal Scences, Vol. 7, 013, no. 45, 9 38 HIKARI Ld, www.m-hkar.com Fuzzy Se Theory n Modelng Uncerany Daa va Inerpolaon Raonal Bezer Surface Funcon Rozam Zakara Deparmen of Mahemacs, Faculy

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu

More information

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm Hqp (,,) = qp Lqq (,,) H p = q H q = p H L = Equvalen o Lagrangan formalsm Smpler, bu wce as

More information

( t) Outline of program: BGC1: Survival and event history analysis Oslo, March-May Recapitulation. The additive regression model

( t) Outline of program: BGC1: Survival and event history analysis Oslo, March-May Recapitulation. The additive regression model BGC1: Survval and even hsory analyss Oslo, March-May 212 Monday May 7h and Tuesday May 8h The addve regresson model Ørnulf Borgan Deparmen of Mahemacs Unversy of Oslo Oulne of program: Recapulaon Counng

More information

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005 Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc

More information

CS286.2 Lecture 14: Quantum de Finetti Theorems II

CS286.2 Lecture 14: Quantum de Finetti Theorems II CS286.2 Lecure 14: Quanum de Fne Theorems II Scrbe: Mara Okounkova 1 Saemen of he heorem Recall he las saemen of he quanum de Fne heorem from he prevous lecure. Theorem 1 Quanum de Fne). Le ρ Dens C 2

More information

Variants of Pegasos. December 11, 2009

Variants of Pegasos. December 11, 2009 Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on

More information

Lecture 6: Learning for Control (Generalised Linear Regression)

Lecture 6: Learning for Control (Generalised Linear Regression) Lecure 6: Learnng for Conrol (Generalsed Lnear Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure 6: RLSC - Prof. Sehu Vjayakumar Lnear Regresson

More information

APPROXIMATE ANALYTIC SOLUTIONS OF A NONLINEAR ELASTIC WAVE EQUATIONS WITH THE ANHARMONIC CORRECTION

APPROXIMATE ANALYTIC SOLUTIONS OF A NONLINEAR ELASTIC WAVE EQUATIONS WITH THE ANHARMONIC CORRECTION THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY Seres A OF THE ROMANIAN ACADEMY Volume 6 Number /5 pp 8 86 APPROXIMATE ANALYTIC SOLUTIONS OF A NONLINEAR ELASTIC WAVE EQUATIONS WITH THE ANHARMONIC

More information

THE GENERALIZED LAGRANGE'S EQUATIONS OF THE SECOND KIND AND THE FIELD METHOD FOR THEIR INTEGRATION UDC Ivana Kovačić

THE GENERALIZED LAGRANGE'S EQUATIONS OF THE SECOND KIND AND THE FIELD METHOD FOR THEIR INTEGRATION UDC Ivana Kovačić FCT UNIVERSITTIS Seres: Mechancs uomac Conrol and Robocs Vol. N o 5 00 pp. - 8 THE GENERLIZED LGRNGE'S EQUTIONS OF THE SECOND KIND ND THE FIELD METHOD FOR THEIR INTEGRTION UDC 5. Ivana Kovačć Faculy of

More information

Scattering at an Interface: Oblique Incidence

Scattering at an Interface: Oblique Incidence Course Insrucor Dr. Raymond C. Rumpf Offce: A 337 Phone: (915) 747 6958 E Mal: rcrumpf@uep.edu EE 4347 Appled Elecromagnecs Topc 3g Scaerng a an Inerface: Oblque Incdence Scaerng These Oblque noes may

More information

Comb Filters. Comb Filters

Comb Filters. Comb Filters The smple flers dscussed so far are characered eher by a sngle passband and/or a sngle sopband There are applcaons where flers wh mulple passbands and sopbands are requred Thecomb fler s an example of

More information

Optimal environmental charges under imperfect compliance

Optimal environmental charges under imperfect compliance ISSN 1 746-7233, England, UK World Journal of Modellng and Smulaon Vol. 4 (28) No. 2, pp. 131-139 Opmal envronmenal charges under mperfec complance Dajn Lu 1, Ya Wang 2 Tazhou Insue of Scence and Technology,

More information

Pendulum Dynamics. = Ft tangential direction (2) radial direction (1)

Pendulum Dynamics. = Ft tangential direction (2) radial direction (1) Pendulum Dynams Consder a smple pendulum wh a massless arm of lengh L and a pon mass, m, a he end of he arm. Assumng ha he fron n he sysem s proporonal o he negave of he angenal veloy, Newon s seond law

More information

On elements with index of the form 2 a 3 b in a parametric family of biquadratic elds

On elements with index of the form 2 a 3 b in a parametric family of biquadratic elds On elemens wh ndex of he form a 3 b n a paramerc famly of bquadrac elds Bora JadrevĆ Absrac In hs paper we gve some resuls abou prmve negral elemens p(c p n he famly of bcyclc bquadrac elds L c = Q ) c;

More information

ON THE WEAK LIMITS OF SMOOTH MAPS FOR THE DIRICHLET ENERGY BETWEEN MANIFOLDS

ON THE WEAK LIMITS OF SMOOTH MAPS FOR THE DIRICHLET ENERGY BETWEEN MANIFOLDS ON THE WEA LIMITS OF SMOOTH MAPS FOR THE DIRICHLET ENERGY BETWEEN MANIFOLDS FENGBO HANG Absrac. We denfy all he weak sequenal lms of smooh maps n W (M N). In parcular, hs mples a necessary su cen opologcal

More information

Some Numerical Methods For Solving Fractional Parabolic Partial Differential Equations

Some Numerical Methods For Solving Fractional Parabolic Partial Differential Equations Eng.& Tech. Journal,Vol.28, No.2, 2 Some Numercal Mehods For Solvng Fraconal Parabolc Paral Dfferenal Dr. Osama H.Mohammed*, Ibsam K.Hanan* & Akram A. Al-Sabbagh* Receved on: 7//29 Acceped on:/4/2 Absrac

More information

Born Oppenheimer Approximation and Beyond

Born Oppenheimer Approximation and Beyond L Born Oppenhemer Approxmaon and Beyond aro Barba A*dex Char Professor maro.barba@unv amu.fr Ax arselle Unversé, nsu de Chme Radcalare LGHT AD Adabac x dabac x nonadabac LGHT AD From Gree dabaos: o be

More information

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times

Reactive Methods to Solve the Berth AllocationProblem with Stochastic Arrival and Handling Times Reacve Mehods o Solve he Berh AllocaonProblem wh Sochasc Arrval and Handlng Tmes Nsh Umang* Mchel Berlare* * TRANSP-OR, Ecole Polyechnque Fédérale de Lausanne Frs Workshop on Large Scale Opmzaon November

More information

An introduction to Support Vector Machine

An introduction to Support Vector Machine An nroducon o Suppor Vecor Machne 報告者 : 黃立德 References: Smon Haykn, "Neural Neworks: a comprehensve foundaon, second edon, 999, Chaper 2,6 Nello Chrsann, John Shawe-Tayer, An Inroducon o Suppor Vecor Machnes,

More information

Testing a new idea to solve the P = NP problem with mathematical induction

Testing a new idea to solve the P = NP problem with mathematical induction Tesng a new dea o solve he P = NP problem wh mahemacal nducon Bacground P and NP are wo classes (ses) of languages n Compuer Scence An open problem s wheher P = NP Ths paper ess a new dea o compare he

More information

Part II CONTINUOUS TIME STOCHASTIC PROCESSES

Part II CONTINUOUS TIME STOCHASTIC PROCESSES Par II CONTINUOUS TIME STOCHASTIC PROCESSES 4 Chaper 4 For an advanced analyss of he properes of he Wener process, see: Revus D and Yor M: Connuous marngales and Brownan Moon Karazas I and Shreve S E:

More information

CHAPTER 10: LINEAR DISCRIMINATION

CHAPTER 10: LINEAR DISCRIMINATION CHAPER : LINEAR DISCRIMINAION Dscrmnan-based Classfcaon 3 In classfcaon h K classes (C,C,, C k ) We defned dscrmnan funcon g j (), j=,,,k hen gven an es eample, e chose (predced) s class label as C f g

More information

Chapter 5. Circuit Theorems

Chapter 5. Circuit Theorems Chaper 5 Crcu Theorems Source Transformaons eplace a olage source and seres ressor by a curren and parallel ressor Fgure 5.-1 (a) A nondeal olage source. (b) A nondeal curren source. (c) Crcu B-conneced

More information

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β

SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β SARAJEVO JOURNAL OF MATHEMATICS Vol.3 (15) (2007), 137 143 SOME NOISELESS CODING THEOREMS OF INACCURACY MEASURE OF ORDER α AND TYPE β M. A. K. BAIG AND RAYEES AHMAD DAR Absrac. In hs paper, we propose

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

A Simple Discrete Approximation for the Renewal Function

A Simple Discrete Approximation for the Renewal Function Busness Sysems Research Vol. 4 No. 1 / March 2013 A Smple Dscree Approxmaon for he Renewal Funcon Alenka Brezavšček Unversy of Marbor, Faculy of Organzaonal Scences, Kranj, Slovena Absrac Background: The

More information

THE method of moment (MOM) is widely used to extract. Fast Green Function Evaluation for Method of Moment. arxiv: v1 [cs.

THE method of moment (MOM) is widely used to extract. Fast Green Function Evaluation for Method of Moment. arxiv: v1 [cs. 1 Fas Green Funcon Evaluaon for Mehod of Momen Shunchuan Yang, Member, IEEE, Dongln Su, Member, IEEE arxv:1901.04162v1 [cs.ce] 14 Jan 2019 Absrac In hs leer, an approach o accelerae he marx fllng n mehod

More information

Lecture VI Regression

Lecture VI Regression Lecure VI Regresson (Lnear Mehods for Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure VI: MLSC - Dr. Sehu Vjayakumar Lnear Regresson Model M

More information