EL-GENDI NODAL GALERKIN METHOD FOR SOLVING LINEAR AND NONLINEAR PARTIAL FRACTIONAL SPACE EQUATIONS

Size: px
Start display at page:

Download "EL-GENDI NODAL GALERKIN METHOD FOR SOLVING LINEAR AND NONLINEAR PARTIAL FRACTIONAL SPACE EQUATIONS"

Transcription

1 Inernon Jorn o es Reserch n Scence nd Technoogy Vome Isse 6: Pge o-7 ovemer-ecemer 3 hp://wwwmnornscom/rshm ISS (Onne): E-GEI OA GAERKI ETO FOR SOVIG IEAR A OIEAR PARTIA FRACTIOA SPACE EQATIOS * E-Kdy Sh E-Syed 3 * e E Sem eprmen o hemcs Fcy o Scence ewn nversy Cro Egyp eprmen o Scenc Compng Fcy o Compers nd Inormcs Benh nversy Benh 358 Egyp 3 eprmen o hemcs Fcy o Scence Benh nversy Benh Egyp Asrc- In hs pper n ecen nmerc echnqe s presened o sove he pr rcon spce eqons wh vre coecens on ne domn Ths echnqe sed on nod Gern mehod The rcon dervves re descred n he Cpo sense Aso y dscree scheme s gven or ype o nonner spce-rcon nomos dvecon-dson eqon In hs pper he proems cn e redced o se o ner gerc eqons y sng he Cheyshev nod Gern mehod The esence nd nqeness o he soon or he ner sem dscree we orm soons re proved And he sy nyss or he ner sem nd y dscree schemes re dscssed merc soons oned y hs mehod re n eceen greemen nd ecen o se wh hose oned y prevos wor n he erre Keywords - Shed Cheyshev poynom; od Gern mehod; Frcon dson eqon; Cpo dervve ITROCTIO In recen yers o o enon hs een devoed o he sdy o rcon deren eqons Frcon dervves rse n mny physc nd engneerng proems sch s eecrc rnsmsson rsonc wve propgon n hmn cnceos one modeng o speech sgns modeng he crdc sse eecrode nerce vscoescy wve propgon n vscoesc horns nd d mechncs [3] nd [3] In hs pper we presen drec compon echnqe or he one-dmenson spce rcon dson eqon o he orm: ( ) ( T () wh n nd homogenos ondry condons s oows: ( ) ( ) ( ( T () he nomos em s he h order rcon dervve o wh respec o he spce vre n he Cpo sense whch w e nrodced er on We wys consder: ( ) re consns The rcon order dson eqons re generzons o cssc dson eqons These eqons py mporn roes n modeng nomos dson nd s-dson sysems descrpon o rcon rndom w ncon o dson nd wve propgon phenomen see eg [] nd he reerences heren ny nmerc nvesgons were crred o y mny hors o sove hs proem In [] he cwrd Eer ne derence scheme s pped n order o on nmerc soons or he eqon Esence nd sy o he pprome soons re crred o y sng he rgh shed Grünwd orm or he rcon dervve erm n he sp drecon In [] ppromon echnqes sed on he shed egendre- de re presened o sove css o n-ondry ve proems or he rcon dson eqons The echnqe s derved y epndng he reqred pprome soon s he eemens o shed egendre poynoms In [] egendre psedo-specr mehod wh he ne derence mehod s sed o on he nmerc soon o he rcon dson eqon Aso we mny sdy one nd o ypc nonner spce-rcon pr deren eqons whch s ced rcon nomos dson nd hs he oowng orm: w ( ( w) w) ( ) w ( w) () T (3) wh n nd ondry condons s oows: w( ) ( ) w( w( T (4) *Correspondng hors: 55 S #7 om Cro Egyp E-m: mm_e_dy@yhoocom *E-m: drhe783@gmcom ISS:78-599

2 Inernon Jorn o es Reserch n Scence nd Technoogy s he h order rcon dervve wh respec m d ( s) o he spce vre n he Cpo sense ow he J ( ) m m ( n ) d ( s) rcon nomos dson ecomes ho opc ecse o s wdey ppcons n he evoon o vros m m m dynmc sysems nder he nence o sochsc orces For empe s we-sed oo or he descrpon o nomos rnspor processes n oh sence nd presence o eern veoces or orce eds oreover he rcon ( m) ( s) nomos dson hve nmeros ppcons n ssc ( ) ds m physcs ophyscs chemsry hydrogeoogy nd oogy ( m ) ( s) see or more des [8][6] nd [7] There re some hors sdyng he spec nomos dson eqon n heorec nyss nd nmerc smons see [6] [4] m ( ) () nd [3] ( ) J ( ) In hs pper we sed E-gend nod Gern mehod whch s eser echnqe hn he s Gern mehod In Gern mehod ech ss poynom chosen ms ssy he ondry condons ndvdy whch cses he Gern ormon o ecome compced prcry when he ondry condons re me-dependen [] Frhermore he presence o nonner erm compces he compon o he sness mr [9] owever he Gern mehod s sed on vron ormon whch preserves essen properes o he connos proem sch s coercvey conny nd symmery o he ner orm nd sy eds o opm error esmes [] On he oher hnd he mn dvnge o he nod Gern mehod s s smpcy nd ey n mpemenon In ddon hs mehod des wh nonner erms more esy hn Gern mehods oreover he proems wh vre coecens nd gener ondry condons re reed s he sme wy s proems wh consn coecens nd smpe ondry condons In c In E-gend Cheyshev nod Gern mehod we sr rom we orm o he eqons we repce hrd o eve negrs y Egend qdrre The orm o E-gend qdrre s ssyng symmerc propery ence we cn redce he nmer o operons o 5% whch mpes o decrese he rondng error Aso E-gend qdrre s n ernng seres whch converges s ( s he nmer o grd pons) The remnder o hs pper s orgnzed s oows: In secon we presen he procedre o soon or he pr rcon spce eqon n ner nd nonner cse In secon 3 we presen he error nyss In secon 4 we gve nmerc epermens o cry he mehod Frcon ervve Spce In hs secon we w gve he rcon dervve spce Frsy we w gve he oowng denons: enon The rcon dervve n he Remnn- ove verson o ncon () s dened s oows [9] ISS: ds An ernve denon nown s he Cpo rcon dervve s: (5) The wo denons re no n gener eqven hey re reed y he oowng reon: ( ) Genery when we consder he rcon deren eqons he Cpo denon s oen preerred snce s esy or mposng n nd ondry condons on cssc dervves B or he Remnn-ove denon hese condons ms e mposed on rcon dervves nd hs s oen no ve So h we w se he Cpo denon n hs pper enon [9] For he rcon dervve spce I ( s dened s oows: I ( { ( : endowed wh he sem-norm: I ( ( nd he norm I ( / I ( ( m m} ( nd e I ( denoes he cosre o C ( ) wh respec o he ove norm nd semnorm enon 3 [5] The rcon spce E ( dened eow E ( { ( : ( ( m m} endowed wh he semnorm / ( nd he norm E ( / E ( ( nd e E ( denoes he cosre o C ( ) wh respec o he ove norm nd semnorm enon 4 [7] For dene he semnorm F( ) ( ( nd he norm ( / ( (

3 Inernon Jorn o es Reserch n Scence nd Technoogy F( ) s he Forer rnsorm o he ncon nd T nd s he me sep whch cn dene noher rcon dervve spce Then eqon (7) s ppromed s oows: Fnd ( e ( e he cosre o C ( wh ( ) / ( ) sch h respec o he ove norm nd semnorm v ( Theorem [7] The spces I ( E ) ( ( ) ( nd ( ) / v v v ( ) (8) ( re eq n he sense h her sem norms s we ( ) e s norms re eqven v ( ) ( ( ) emm [6 (Frcon Poncré Fredrchs)] nd For ( we hve F( v ( g hen he sem-dscree proem (8) cn e wren n smpe C orm e h: ( ( ( ) / F( v ( ) (9) nd or m / m Z C ( ( emm [7] For I ( ) hen ( ) ( ) 3 ERICA TREATEETS FOR TE PARTIAFRACTIOA SPACE In hs secon we presen he nmerc soon or me spce rcon ner nd nonner eqons respecvey he spce rcon dervve s he Cpo dervve 3 E-GEI OA GAERKI ETO FOR IEAR CASE Ths mehod srs wh he we orm nd he r spce concdes wh he es ncon spce The we orm o proem () nd () n cse s gven s oows: ( ) / Fnd ( ) sch h v ( ) ( ( ) ( v ( ) / v ( ) (7) he nner prodc vs dened s v ( ) v( ) d e we w prove he esence nd nqeness o he we orm (7) So we gve he properes o he rcon dson operor whch s gven n [4] s oows: - ( ) ( ) ) ( ) / ( / on ) ( ) - ) v ( ) ) ( v v ( ) / ( ) / coercvy ( conny on ) / ( / ( ) ) ( ) re consns Appyng he mpc Eer ppromon o pprome he me dervve we dene Theorem (Esence nd nqeness) For ( ) nd or sceny sm sep sze here ess nqe soon ssyng (9) Proo Frsy we w prove he coercvy o he ner orm y sng he properes o he rcon dson operor nd Frcon Poncré Fredrchs neqy ) ( ) ( ( ( ) )) C ( ) ( ) / ( ) ( ) / ( ) ( / hen ner orm ) s coercve over ) ( ) e we w prove he conny o he ner orm ( ) over ) / ( / ( ) ) ( ) s oows: ( ( v ( ) ( ) C ( ( ) ) ( ) / ( / ( ) ) ( ) ( ) / ( ) v v ( ) / ( ) oreover we cn so prove he conny o F() ( ) / ( ) s oows: F ( ( g g v ( ) ( ) C g v ( ) / ( ) ( ) / ( ) over Thereore he hypoheses o -grm heorem re ssed [4] nd hen here es nqe soon or he sem-dscree we orm (9) Theorem 3 (Sy o he sem-dscree proem) For ( ) nd or sceny sm sep sze he proem (9) s se nd hods ISS:78-599

4 Inernon Jorn o es Reserch n Scence nd Technoogy o ensre he ppromons ssy he ondry condons ( ) / ( ) ( ) ( ) we se Aso snce he es ncon v() s Proo For nd v hen proem (8) w e ncon o h order poynoms so we cn wre hese poynoms n he eqven crdn orm ( ) ( ( ) ) v( ) v V ( ) () The rgh hnd sde o () w e he nod ves V re rrry ecep h ( ) ( ( ) ) V V o ensre h v sses he ondry C ( ) / () condons ow he dscree we orm s gven s oows: ( ) nd P The e hnd sde o () v ( ) ( ) v ( ) ( ) (From emm ) ( ) ( ) ( ) ( ) ( ) C () ( ) / ( ) ( ) ( ) From () nd () we hve C ( ) / (3) ( ) C ( ) ( ) For so we hve ( ) / C ( ) 3 (4) ( ) ( ) From (3) (4) we on ( ) / C ( ) 4 ( ) ( ) ow E-gend nod Gern mehod dscrezon proceeds y ppromng he soon he poynoms o hgh degree So we nrodce ne dmenson spce ( ) / P P ( ) P s he spce o poynoms n whch he poynom degree s ess hn or eq o nd he spce s gven s oows P spn ( ) ( ) } { ( ) re gven y: ( ) T ((/ ) or ecep / nd ) T ((/ ) ) (5) ( ) The grd pons re he erem pons o he shed Cheyshev poynom T (( / ) ) e he pprome soon s gven s oows ( ( ( ( ) (6) v P (7) he nner prodc g h s eved s oows g( ) h( ) g h nd ( y ) y cos The qnes re gven y: [9] / 4 s cos 4 (8) Snce hen he mpped weghs w e gven rom he oowng reon Then he rs dscree nner prodc ecomes v nn ( ) Vm m( ) n m snce ( ) hen he sm redces o v V (9) d d For evng he second erm n (7) e ( ) ( ) hen he rcon dervve o he crdn ncon cn e wren ( ) T (( / ) ) T ((/ ) ) s: ISS:

5 ( y ) y cos nd he Cpo rcon dervve o he Shed Cheyshev poynom s: T ((/ ) ) T (( / ) ) d ( ) ( ) or he dervves o Cheyshev poynom T ssy T T T T T T T 4 ( ) ( ) so we cn dedce h he recrrence reons T T ( ) T T 3 T even () T ( T T 3 5T ) odd () Then rom eq (-) we cn dedce he orgn mod derenon mr n he specr spce s sprse pper rngr mr wh neres d ( ) even oherwse Then he Cpo rcon dervve o he Shed Cheyshev poynom s [4]nd gven s oows: ( ) ( / ) ( ) (3) ( ) ( )( ) ( ) 3 4( / ) 4(/ ) ( ) (4) (3 )( )( ) ( )( ) ( ) nd or n 3 4 we hve he oowng recrrence reon ( ( )) ((/ ) )( ( )) ( ) ( ( )) (5) ( ) hence y ssng (3) (4) nd (5) n () hen we hve T ((/ ) ) dn n( ) (6) ( ) n Conseqeny he rcon dervve o he crdn ncon s gven n he oowng orm: ( ) T ((/ ) ) dn n( ) ( ) n The second erm n () cn e eved s oows: ( )( ) V ( [ ( )( ( ) ( ) Inernon Jorn o es Reserch n Scence nd Technoogy he rs dervve o he crdn ncons () ( ) ( ))]) (7) he pons s derved n [] Smry he sorce erm s gven s oows: v V (8) From eqons (9) (7) nd (8) we hve V ( [ ( )[ ( ) ( ) ( ) ( )]] Snce V s re nery ndependen he coecen o ech V ms e zero so nd ( B [ C ( )( ( ) ( ) ( ) ( ))] ) (9) B ( ) ( ) ( ) C ( ) ( ) e A B C ) hen (9) cn e wren s ( A wh he ondry condons Then he y dscree proem s gven n he oowng orm A wh he ondry condons (3) 3 STABIITY FOR F ISCRETE PROBE In hs secon we se rec ery-schder ed pon heorem [8] o prove he esence o he soon or eq (3) n emm 3 For gven open nd onded domn R n connng he orgn nd e : R e connos ncon I ( ) or nd hen hs ed pon n whch s he cosre o We nrodce dscree norm whch ndced rom he dscree nner prodc ISS:

6 Inernon Jorn o es Reserch n Scence nd Technoogy / y he dscree Gronw neqy we on g g g ( ) ( ) g g CT ep A Theorem 4 The eqon (3) hs soon n Proo e B ( ) R e cenered he orgn wh rds nd consder e he ondry o e ( ) e vecor on he ondry sch h or some E ( ) (3) E ( ) A y ng dscree nner prodc o (3) wh hen we hve ( E ( ) ) ( ) ( ) ( A ) ( ) ( ) rom [] nd snce ( s connos on [ ] [ T ] hen y Gronw emm we hve: nd y ppyng Cshy-Schwrz neqy we hve A (3) A s onded y posve nmer vde oh sdes o (3) y A hen we hve hen or rge nd or very sm hen whch mpes o conrdcon So E ( ) ence here s soon sch h E ) ( Theorem 5 For ny ed he dscree scheme (3) s se Proo From eqon (3) nd y ng dscree nner prodc wh nd snce Then rom Cshy-Schwrz neqy we hve A (33) hen y smmng (33) rom o A we on ISS: OIEAR CASE In hs secon we w sre how we cn se he nod Cheyshev Gern mehod o sove he nonner dson eqon So we w gve he we orm o proem (3) nd (4) n cse s gven s oows: Fnd ( ) / ( ) sch h: w v ( ( w) w) v w ( ( / ( w) v v ) ( ) The esence nd nqeness o he we orm s proved n [3] e he pprome soon s gven s oows: w( w ( W ( ( ) so he ove we orm cn e wren s w v ( ( w ) w ) v w ( ( w ) v v P Aer some mnpons we hve W B W C W B W ( w C ( ) ( ) ( ) ( ) ( w ) ) ( ) ( ) nd hence (35) s gven s W B W A W ) (34) (35) ( w (36) A C To pprome he me dervve we w se he cwrd Eer ne derence or he ner prs whe he orwrd Eer ne derence or he nonner pr e s he ppromon o ) Then (36) s ppromed y ( W A W W [ ( W ) ( ( W ) wh he ondry condons )]

7 Inernon Jorn o es Reserch n Scence nd Technoogy W W (37) 4 ERICA EXPERIAETS In hs secon we w gve nmerc empes nd we w se ATAB 8 sowre o on he nmerc ress Empe : Consder he oowng spce rcon order deren eqon: ( () 8 ) 8 ( 3 ( (6 3 ) e wh he n nd ondry condons: 3 ( ) ( ) ( ( T 3 The ec soon s ( ( ) e The nmerc ress re shown n e nd gres In e we gve he soe errors eween he ec soon ( nd he pprome soon ( ) nd we me comprson wh ress oned y mehod n [] he neror pons n me T wh me sep 5 TABE : The soe error eween he ec nd pprome soons n he neror pons T X od ehod [] ehod 533 e-6 4 e-5 86 e e e e e-6 37 e e-6 36 e e-6 94 e e-6 95 e e-6 49 e e-7 83 e-5 ppro 5 I s noed rom Te nd Fg h we cn cheve good ppromon or he ec soon y sng E-gend Gern mehod nd so or ress re n good greemen wh he mehod nrodced n [] Empe : Consder he oowng nonner spce rcon order deren eqon [3]: w ( w d ( e 5 w) d( w w ( w 5 5 ( ) (5) (5) 5 5 ( e (5) (5) wh he n nd ondry condons: w( ) ( ) w ( w( In hs cse he ec soon s ( ) e ( ) The nmerc ress re shown n e nd gre In e we gve he mmm error eween he ec soon w ( nd he pprome soon w ( n he neror pons wh deren me seps oe h he mmm error s dened s oows: w( w ( w w m TABE : The mmm error or T T 3 T 5 T 56 e-3 8 e-3 39 e-4 6 e-6 6 e e-4 79 e-5 69 e e e-4 58 e e e e-4 5 e e-7 Ec () ( Fg: () po o he pprome soon ( po o he ec soon or 3 nd TABE 3: The comprson eween E-gend nod Gern nd psedo-specr mehods or deren nd me T 5 3 od ehod Psedo ehod od ehod Psedo ehod 394 e e e e-4 75 e-5 37 e-4 7 e-5 4 e e-5 e-4 55 e-5 6 e e-5 99 e e-5 3 e-4 ISS:

8 W( W( () Fg () Psedo ehod T 5 Inernon Jorn o es Reserch n Scence nd Technoogy REFERECES Ec Psedo Ec od ( nd 3 ( E-gend od mehod T 5 nd 3 I s cer rom e when he me sep e smer; we on good ccrcy hogh or ong me On he oher hnd n e 3 we me comprson eween he nod mehod nd he psedo-specr mehod or consn n me nd or deren nmer o grd pons deren me seps We noe h he me sep 4 nd or he mmm error o he nod mehod s ( 5 e-5) oreover when he nmer o grd pons ncresed ( 3 ) he mmm error decrese o rech (337e-5) owever psedo-specr mehod he sme me sep nd when he nmer o grd pons ncresed he mmm error ncresed rom (99 e-5) o (3 e-4) Aso we cn oserve h rom Fgre whch ensres or nmerc ress So or mehod s convergen nd se n he nmerc sense 5 COCSIO In hs rce we propose new echnqe or sovng ner nd nonner rcon dvecon-dson eqon nmercy The mehod sed on he Cheyshev poynom nd he rcon dervves re descred n he Cpo sense The soon oned sng he proposed mehod shows h hs pproch cn sove he proem eecvey Comprsons re mde eween he pprome nd ec soons sre he vdy nd he gre poen o he proposed echnqe ACKOWEGET We e o epress sncere pprecon nd deep grde o prcpns n hs wor Boyd JP Cheyshev nd Forer specr mehods over neo Cho W Chng S K ee Y J merc soons or spcercon dsperson eqons wh nonner sorce erms B Koren h Soc r Bshor Appcons o rcon ccs App h Sc ehem K The Anyss o Frcon eren Eqons: An Appcon-Orened Eposon sng eren Operors o Cpo Type Sprnger 4 5 Erry E E-Syed gher order psedospecr derenon mrces Apped merc hemcs Ervn V J eer Roop J P merc ppromon o me dependen nonner spcercon dson eqon SIA Jorn on merc Anyss 45 () Ervn VJ Roop JP Vron ormon or he sonry rcon dvecon dsperson eqon mer eh Pr E (3) enry B I ngnds T A Werne S Anomos dson wh ner recon dynmcs: rom connos me rndom ws o rcon recon-dson eqons Physc Revew E rce (3) 6 9 eshven JS Goe S Goe Specr ehods or Tme-ependen Proems The Cmrdge monogrphs on pped nd compon mhemcs 7 Khder Swem hdy AS An ecen nmerc mehod or sovng he rcon dson eqon Jorn o Apped hemcs & Bonormcs - Kher A Temsh RS ssn A Cheyshev specr coocon mehod or sovng Brgers -ype eqons J o compon nd pped mhemcs Khder On he nmerc soons or he rcon dson eqon Commn onner Sc mer Sm Ks AA Srvsv Tro JJ Theory nd Appcons o Frcon eren Eqons Esever Sn ego 6 4 C P Zho Z G Chen Y Q merc ppromon o nonner rcon deren eqons wh sdson nd sperdson Compers & hemcs wh Appcons XJ X CJ A spce-me specr mehod or he me rcon deren eqon SIA J mer An 47(3) gn R Adh O Ben Zho X J Anomos dson epressed hrogh rcon order deren operors n he Boch-Torrey eqon Jorn o gnec Resonnce 9 () eerscher Benson A Bemer B Operor evy moon nd mscng nomos dson Physc Revew E rce 63 (I) 8 Oreg J Rhenod W C Ierve Soon o onner Eqons n Sever Vres Acdemc Press ew Yor- ondon 97 9 Podny I Frcon eren Eqons vo 98 Acdemc Press Sn ego C SA 999 Ry SS Anyc soon or he spce rcon dson eqon y wo-sep Adomn decomposon mehod Commn onner Sc mer Sm Sdmnd A ehghn A pproch or soon o he spce rcon dson eqon Compers nd hemcs wh Appcons Shen J Tng T Specr nd gh-order ehods wh Appcons Scence Press o Chn 6 3 Zheng Y Zho Z A y dscree Gern mehod or nonner Spce-rcon dson Eqon hemc Proems n Engneerng Arce 76 pges ISS:

The Characterization of Jones Polynomial. for Some Knots

The Characterization of Jones Polynomial. for Some Knots Inernon Mhemc Forum,, 8, no, 9 - The Chrceron of Jones Poynom for Some Knos Mur Cncn Yuuncu Y Ünversy, Fcuy of rs nd Scences Mhemcs Deprmen, 8, n, Turkey m_cencen@yhoocom İsm Yr Non Educon Mnsry, 8, n,

More information

1.B Appendix to Chapter 1

1.B Appendix to Chapter 1 Secon.B.B Append o Chper.B. The Ordnr Clcl Here re led ome mporn concep rom he ordnr clcl. The Dervve Conder ncon o one ndependen vrble. The dervve o dened b d d lm lm.b. where he ncremen n de o n ncremen

More information

REPORT No. 1/9_10_01 ROBUST ADAPTIVE CONTROL OF LINEARIZABLE NONLINEAR SINGLE INPUT SYSTEMS *

REPORT No. 1/9_10_01 ROBUST ADAPTIVE CONTROL OF LINEARIZABLE NONLINEAR SINGLE INPUT SYSTEMS * REPORT No. 9_0_0 ROBUT ADAPTIVE CONTROL OF LINEARIZABLE NONLINEAR INGLE INPUT YTEM * Hojn X n Peros A. Ionno Deprmen o Eecrc Enneern - ysems Unersy o ohern Corn Los Anees CA 90089-56 Asrc: The esn o szn

More information

Stochastic Programming handling CVAR in objective and constraint

Stochastic Programming handling CVAR in objective and constraint Sochasc Programmng handlng CVAR n obecve and consran Leondas Sakalaskas VU Inse of Mahemacs and Informacs Lhana ICSP XIII Jly 8-2 23 Bergamo Ialy Olne Inrodcon Lagrangan & KKT condons Mone-Carlo samplng

More information

NUMERICAL SOLUTION OF THIN FILM EQUATION IN A CLASS OF DISCONTINUOUS FUNCTIONS

NUMERICAL SOLUTION OF THIN FILM EQUATION IN A CLASS OF DISCONTINUOUS FUNCTIONS Eropen Scenfc Jornl Ags 5 /SPECAL/ eon SSN: 857 788 Prn e - SSN 857-74 NMERCAL SOLON OF HN FLM EQAON N A CLASS OF DSCONNOS FNCONS Bn Snsoysl Assoc Prof Mr Rslov Prof Beyen nversy Deprmen of Memcs n Compng

More information

Different kind of oscillation

Different kind of oscillation PhO 98 Theorecal Qeson.Elecrcy Problem (8 pons) Deren knd o oscllaon e s consder he elecrc crc n he gre, or whch mh, mh, nf, nf and kω. The swch K beng closed he crc s copled wh a sorce o alernang crren.

More information

PHYS 1443 Section 001 Lecture #4

PHYS 1443 Section 001 Lecture #4 PHYS 1443 Secon 001 Lecure #4 Monda, June 5, 006 Moon n Two Dmensons Moon under consan acceleraon Projecle Moon Mamum ranges and heghs Reerence Frames and relae moon Newon s Laws o Moon Force Newon s Law

More information

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9 C C A 55NED n R 5 0 9 b c c \ { s AS EC 2 5? 9 Con 0 \ 0265 o + s ^! 4 y!! {! w Y n < R > s s = ~ C c [ + * c n j R c C / e A / = + j ) d /! Y 6 ] s v * ^ / ) v } > { ± n S = S w c s y c C { ~! > R = n

More information

THE EXISTENCE OF SOLUTIONS FOR A CLASS OF IMPULSIVE FRACTIONAL Q-DIFFERENCE EQUATIONS

THE EXISTENCE OF SOLUTIONS FOR A CLASS OF IMPULSIVE FRACTIONAL Q-DIFFERENCE EQUATIONS Europen Journl of Mhemcs nd Compuer Scence Vol 4 No, 7 SSN 59-995 THE EXSTENCE OF SOLUTONS FOR A CLASS OF MPULSVE FRACTONAL Q-DFFERENCE EQUATONS Shuyun Wn, Yu Tng, Q GE Deprmen of Mhemcs, Ynbn Unversy,

More information

SVMs for regression Non-parametric/instance based classification method

SVMs for regression Non-parametric/instance based classification method S 75 Mchne ernng ecture Mos Huskrecht mos@cs.ptt.edu 539 Sennott Squre SVMs for regresson Non-prmetrc/nstnce sed cssfcton method S 75 Mchne ernng Soft-mrgn SVM Aos some fet on crossng the seprtng hperpne

More information

EEM 486: Computer Architecture

EEM 486: Computer Architecture EEM 486: Compuer Archecure Lecure 4 ALU EEM 486 MIPS Arhmec Insrucons R-ype I-ype Insrucon Exmpe Menng Commen dd dd $,$2,$3 $ = $2 + $3 sub sub $,$2,$3 $ = $2 - $3 3 opernds; overfow deeced 3 opernds;

More information

Supporting information How to concatenate the local attractors of subnetworks in the HPFP

Supporting information How to concatenate the local attractors of subnetworks in the HPFP n Effcen lgorh for Idenfyng Prry Phenoype rcors of Lrge-Scle Boolen Newor Sng-Mo Choo nd Kwng-Hyun Cho Depren of Mhecs Unversy of Ulsn Ulsn 446 Republc of Kore Depren of Bo nd Brn Engneerng Kore dvnced

More information

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005.

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005. Techc Appedx fo Iveoy geme fo Assemy Sysem wh Poduc o Compoe eus ecox d Zp geme Scece 2005 Lemm µ µ s c Poof If J d µ > µ he ˆ 0 µ µ µ µ µ µ µ µ Sm gumes essh he esu f µ ˆ > µ > µ > µ o K ˆ If J he so

More information

Jordan Journal of Physics

Jordan Journal of Physics Volume, Number, 00. pp. 47-54 RTICLE Jordn Journl of Physcs Frconl Cnoncl Qunzon of he Free Elecromgnec Lgrngn ensy E. K. Jrd, R. S. w b nd J. M. Khlfeh eprmen of Physcs, Unversy of Jordn, 94 mmn, Jordn.

More information

Support vector machines for regression

Support vector machines for regression S 75 Mchne ernng ecture 5 Support vector mchnes for regresson Mos Huskrecht mos@cs.ptt.edu 539 Sennott Squre S 75 Mchne ernng he decson oundr: ˆ he decson: Support vector mchnes ˆ α SV ˆ sgn αˆ SV!!: Decson

More information

UNIVERSAL BOUNDS FOR EIGENVALUES OF FOURTH-ORDER WEIGHTED POLYNOMIAL OPERATOR ON DOMAINS IN COMPLEX PROJECTIVE SPACES

UNIVERSAL BOUNDS FOR EIGENVALUES OF FOURTH-ORDER WEIGHTED POLYNOMIAL OPERATOR ON DOMAINS IN COMPLEX PROJECTIVE SPACES wwwrresscom/volmes/vol7isse/ijrras_7 df UNIVERSAL BOUNDS FOR EIGENVALUES OF FOURTH-ORDER WEIGHTED POLYNOIAL OPERATOR ON DOAINS IN COPLEX PROJECTIVE SPACES D Feng & L Ynl * Scool of emcs nd Pyscs Scence

More information

Review: Transformations. Transformations - Viewing. Transformations - Modeling. world CAMERA OBJECT WORLD CSE 681 CSE 681 CSE 681 CSE 681

Review: Transformations. Transformations - Viewing. Transformations - Modeling. world CAMERA OBJECT WORLD CSE 681 CSE 681 CSE 681 CSE 681 Revew: Trnsforons Trnsforons Modelng rnsforons buld cople odels b posonng (rnsforng sple coponens relve o ech oher ewng rnsforons plcng vrul cer n he world rnsforon fro world coordnes o cer coordnes Perspecve

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

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9

OH BOY! Story. N a r r a t iv e a n d o bj e c t s th ea t e r Fo r a l l a g e s, fr o m th e a ge of 9 OH BOY! O h Boy!, was or igin a lly cr eat ed in F r en ch an d was a m a jor s u cc ess on t h e Fr en ch st a ge f or young au di enc es. It h a s b een s een by ap pr ox i ma t ely 175,000 sp ect at

More information

Physics 201 Lecture 2

Physics 201 Lecture 2 Physcs 1 Lecure Lecure Chper.1-. Dene Poson, Dsplcemen & Dsnce Dsngush Tme nd Tme Inerl Dene Velocy (Aerge nd Insnneous), Speed Dene Acceleron Undersnd lgebrclly, hrough ecors, nd grphclly he relonshps

More information

Chapter 6. Isoparametric Formulation

Chapter 6. Isoparametric Formulation ME 78 FIIE ELEME MEHOD Chper. Ioprerc Forlon Se fncon h ed o defne he eleen geoer ed o defne he dplceen whn he eleen ode r Eleen Lner geoer Lner dplceen ode Be Eleen Qdrc geoer Qdrc dplceen We gn he e

More information

Nuclear/Particle Physics

Nuclear/Particle Physics Revsc Prce Dyncs: The Bsc de o Qunu Fed Theory n Prce Physcs: Progresson o seps n he heorec rewor up o now: Revsc Prces Drc eqn. = ½ K-G eqn. = 0 resus n posve nd negve energy souons Expnd Drc nd K-G sons.

More information

Chapter 6 DETECTION AND ESTIMATION: Model of digital communication system. Fundamental issues in digital communications are

Chapter 6 DETECTION AND ESTIMATION: Model of digital communication system. Fundamental issues in digital communications are Chaper 6 DCIO AD IMAIO: Fndaenal sses n dgal concaons are. Deecon and. saon Deecon heory: I deals wh he desgn and evalaon of decson ang processor ha observes he receved sgnal and gesses whch parclar sybol

More information

SVMs for regression Multilayer neural networks

SVMs for regression Multilayer neural networks Lecture SVMs for regresson Muter neur netors Mos Husrecht mos@cs.ptt.edu 539 Sennott Squre Support vector mchne SVM SVM mmze the mrgn round the seprtng hperpne. he decson functon s fu specfed suset of

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

4. Runge-Kutta Formula For Differential Equations

4. Runge-Kutta Formula For Differential Equations NCTU Deprme o Elecrcl d Compuer Egeerg 5 Sprg Course by Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos To solve e derel equos umerclly e mos useul ormul s clled Ruge-Ku ormul

More information

, t 1. Transitions - this one was easy, but in general the hardest part is choosing the which variables are state and control variables

, t 1. Transitions - this one was easy, but in general the hardest part is choosing the which variables are state and control variables Opmal Conrol Why Use I - verss calcls of varaons, opmal conrol More generaly More convenen wh consrans (e.g., can p consrans on he dervaves More nsghs no problem (a leas more apparen han hrogh calcls of

More information

Integral Equations and their Relationship to Differential Equations with Initial Conditions

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

More information

Chapters 2 Kinematics. Position, Distance, Displacement

Chapters 2 Kinematics. Position, Distance, Displacement Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen

More information

Chapter 2. Review of Hydrodynamics and Vector Analysis

Chapter 2. Review of Hydrodynamics and Vector Analysis her. Ree o Hdrodmcs d Vecor Alss. Tlor seres L L L L ' ' L L " " " M L L! " ' L " ' I s o he c e romed he Tlor seres. O he oher hd ' " L . osero o mss -dreco: L L IN ] OUT [mss l [mss l] mss ccmled h me

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

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

A finite difference method for heat equation in the unbounded domain

A finite difference method for heat equation in the unbounded domain Internatona Conerence on Advanced ectronc Scence and Technoogy (AST 6) A nte derence method or heat equaton n the unbounded doman a Quan Zheng and Xn Zhao Coege o Scence North Chna nversty o Technoogy

More information

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings.

THIS PAGE DECLASSIFIED IAW EO IRIS u blic Record. Key I fo mation. Ma n: AIR MATERIEL COMM ND. Adm ni trative Mar ings. T H S PA G E D E CLA SSFED AW E O 2958 RS u blc Recod Key fo maon Ma n AR MATEREL COMM ND D cumen Type Call N u b e 03 V 7 Rcvd Rel 98 / 0 ndexe D 38 Eneed Dae RS l umbe 0 0 4 2 3 5 6 C D QC d Dac A cesson

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

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

Minimum Squared Error

Minimum Squared Error Minimum Squred Error LDF: Minimum Squred-Error Procedures Ide: conver o esier nd eer undersood prolem Percepron y i > for ll smples y i solve sysem of liner inequliies MSE procedure y i = i for ll smples

More information

Minimum Squared Error

Minimum Squared Error Minimum Squred Error LDF: Minimum Squred-Error Procedures Ide: conver o esier nd eer undersood prolem Percepron y i > 0 for ll smples y i solve sysem of liner inequliies MSE procedure y i i for ll smples

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

4.8 Improper Integrals

4.8 Improper Integrals 4.8 Improper Inegrls Well you ve mde i hrough ll he inegrion echniques. Congrs! Unforunely for us, we sill need o cover one more inegrl. They re clled Improper Inegrls. A his poin, we ve only del wih inegrls

More information

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula NCTU Deprme o Elecrcl d Compuer Egeerg Seor Course By Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos A. Euler Formul B. Ruge-Ku Formul C. A Emple or Four-Order Ruge-Ku Formul

More information

1. Introduction. ) only ( See theorem

1. Introduction. ) only ( See theorem O Sovbiiy or Higher Order Prboic Eqios Mrí López Mores Deprme o Comper Sciece Moerrey Isie o echoogy Meico Ciy Cmps Ce de PeeNo Ejidos de HipcopCP438 Meico DF MEXICO Absrc: - We cosider he Cchy probem

More information

-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL

-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL UPB Sc B See A Vo 72 I 3 2 ISSN 223-727 MUTIPE -HYBRID APACE TRANSORM AND APPICATIONS TO MUTIDIMENSIONA HYBRID SYSTEMS PART II: DETERMININ THE ORIINA Ve PREPEIŢĂ Te VASIACHE 2 Ace co copeeă oă - pce he

More information

A NEW INTERPRETATION OF INTERVAL-VALUED FUZZY INTERIOR IDEALS OF ORDERED SEMIGROUPS

A NEW INTERPRETATION OF INTERVAL-VALUED FUZZY INTERIOR IDEALS OF ORDERED SEMIGROUPS ScInLhore),7),9-37,4 ISSN 3-536; CODEN: SINTE 8 9 A NEW INTERPRETATION O INTERVAL-VALUED UZZY INTERIOR IDEALS O ORDERED SEMIGROUPS Hdy Ullh Khn, b, Nor Hnz Srmn, Asghr Khn c nd z Muhmmd Khn d Deprmen of

More information

CONSISTENT EARTHQUAKE ACCELERATION AND DISPLACEMENT RECORDS

CONSISTENT EARTHQUAKE ACCELERATION AND DISPLACEMENT RECORDS APPENDX J CONSSTENT EARTHQUAKE ACCEERATON AND DSPACEMENT RECORDS Earhqake Acceleraons can be Measred. However, Srcres are Sbjeced o Earhqake Dsplacemens J. NTRODUCTON { XE "Acceleraon Records" }A he presen

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

II The Z Transform. Topics to be covered. 1. Introduction. 2. The Z transform. 3. Z transforms of elementary functions

II The Z Transform. Topics to be covered. 1. Introduction. 2. The Z transform. 3. Z transforms of elementary functions II The Z Trnsfor Tocs o e covered. Inroducon. The Z rnsfor 3. Z rnsfors of eleenry funcons 4. Proeres nd Theory of rnsfor 5. The nverse rnsfor 6. Z rnsfor for solvng dfference equons II. Inroducon The

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

Mathematics 805 Final Examination Answers

Mathematics 805 Final Examination Answers . 5 poins Se he Weiersrss M-es. Mhemics 85 Finl Eminion Answers Answer: Suppose h A R, nd f n : A R. Suppose furher h f n M n for ll A, nd h Mn converges. Then f n converges uniformly on A.. 5 poins Se

More information

MODEL SOLUTIONS TO IIT JEE ADVANCED 2014

MODEL SOLUTIONS TO IIT JEE ADVANCED 2014 MODEL SOLUTIONS TO IIT JEE ADVANCED Pper II Code PART I 6 7 8 9 B A A C D B D C C B 6 C B D D C A 7 8 9 C A B D. Rhc(Z ). Cu M. ZM Secon I K Z 8 Cu hc W mu hc 8 W + KE hc W + KE W + KE W + KE W + KE (KE

More information

0# E % D 0 D - C AB

0# E % D 0 D - C AB 5-70,- 393 %& 44 03& / / %0& / / 405 4 90//7-90/8/3 ) /7 0% 0 - @AB 5? 07 5 >0< 98 % =< < ; 98 07 &? % B % - G %0A 0@ % F0 % 08 403 08 M3 @ K0 J? F0 4< - G @ I 0 QR 4 @ 8 >5 5 % 08 OF0 80P 0O 0N 0@ 80SP

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary

More information

Research on Negotiation based Bargaining Strategies in e-commerce Jiang Jianhua 1,a, Zhang Guangyun 1,b, Hong Niansong 2,c

Research on Negotiation based Bargaining Strategies in e-commerce Jiang Jianhua 1,a, Zhang Guangyun 1,b, Hong Niansong 2,c Inernon Conference on Apped Scence nd Engneerng Innovon (ASEI 05) Reserch on egoon sed Brgnng Sreges n e-commerce Jng Jnhu,, Zhng Gungyun,, Hong nsong,c Coege of Compuer Engneerng, Gungdong Insue of Scence

More information

Displacement, Velocity, and Acceleration. (WHERE and WHEN?)

Displacement, Velocity, and Acceleration. (WHERE and WHEN?) Dsplacemen, Velocy, and Acceleraon (WHERE and WHEN?) Mah resources Append A n your book! Symbols and meanng Algebra Geomery (olumes, ec.) Trgonomery Append A Logarhms Remnder You wll do well n hs class

More information

Variational method to the second-order impulsive partial differential equations with inconstant coefficients (I)

Variational method to the second-order impulsive partial differential equations with inconstant coefficients (I) Avalable onlne a www.scencedrec.com Proceda Engneerng 6 ( 5 4 Inernaonal Worksho on Aomoble, Power and Energy Engneerng Varaonal mehod o he second-order mlsve aral dfferenal eqaons wh nconsan coeffcens

More information

Calculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( )

Calculus 241, section 12.2 Limits/Continuity & 12.3 Derivatives/Integrals notes by Tim Pilachowski r r r =, with a domain of real ( ) Clculu 4, econ Lm/Connuy & Devve/Inel noe y Tm Plchow, wh domn o el Wh we hve o : veco-vlued uncon, ( ) ( ) ( ) j ( ) nume nd ne o veco The uncon, nd A w done wh eul uncon ( x) nd connuy e he componen

More information

Solutions to Problems from Chapter 2

Solutions to Problems from Chapter 2 Soluions o Problems rom Chper Problem. The signls u() :5sgn(), u () :5sgn(), nd u h () :5sgn() re ploed respecively in Figures.,b,c. Noe h u h () :5sgn() :5; 8 including, bu u () :5sgn() is undeined..5

More information

Decompression diagram sampler_src (source files and makefiles) bin (binary files) --- sh (sample shells) --- input (sample input files)

Decompression diagram sampler_src (source files and makefiles) bin (binary files) --- sh (sample shells) --- input (sample input files) . Iroduco Probblsc oe-moh forecs gudce s mde b 50 esemble members mproved b Model Oupu scs (MO). scl equo s mde b usg hdcs d d observo d. We selec some prmeers for modfg forecs o use mulple regresso formul.

More information

WebAssign HW Due 11:59PM Tuesday Clicker Information

WebAssign HW Due 11:59PM Tuesday Clicker Information WebAssgn HW Due 11:59PM Tuesday Clcker Inormaon Remnder: 90% aemp, 10% correc answer Clcker answers wll be a end o class sldes (onlne). Some days we wll do a lo o quesons, and ew ohers Each day o clcker

More information

Background and Motivation: Importance of Pressure Measurements

Background and Motivation: Importance of Pressure Measurements Imornce of Pressre Mesremens: Pressre s rmry concern for mny engneerng lcons e.g. lf nd form drg. Cvon : Pressre s of fndmenl mornce n ndersndng nd modelng cvon. Trblence: Velocy-Pressre-Grden ensor whch

More information

Chapter 6 Plane Motion of Rigid Bodies

Chapter 6 Plane Motion of Rigid Bodies Chpe 6 Pne oon of Rd ode 6. Equon of oon fo Rd bod. 6., 6., 6.3 Conde d bod ced upon b ee een foce,, 3,. We cn ume h he bod mde of e numbe n of pce of m Δm (,,, n). Conden f he moon of he m cene of he

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

P-Convexity Property in Musielak-Orlicz Function Space of Bohner Type

P-Convexity Property in Musielak-Orlicz Function Space of Bohner Type J N Sce & Mh Res Vol 3 No (7) -7 Alble ole h://orlwlsogocd/deh/sr P-Coey Proery Msel-Orlcz Fco Sce o Boher ye Yl Rodsr Mhecs Edco Deree Fcly o Ss d echology Uerss sl Neger Wlsogo Cerl Jdoes Absrcs Corresodg

More information

CHAPTER 7: CLUSTERING

CHAPTER 7: CLUSTERING CHAPTER 7: CLUSTERING Semparamerc Densy Esmaon 3 Paramerc: Assume a snge mode for p ( C ) (Chapers 4 and 5) Semparamerc: p ( C ) s a mure of denses Mupe possbe epanaons/prooypes: Dfferen handwrng syes,

More information

Research Article Oscillatory Criteria for Higher Order Functional Differential Equations with Damping

Research Article Oscillatory Criteria for Higher Order Functional Differential Equations with Damping Journl of Funcon Spces nd Applcons Volume 2013, Arcle ID 968356, 5 pges hp://dx.do.org/10.1155/2013/968356 Reserch Arcle Oscllory Crer for Hgher Order Funconl Dfferenl Equons wh Dmpng Pegung Wng 1 nd H

More information

Chapter 2 Linear Mo on

Chapter 2 Linear Mo on Chper Lner M n .1 Aerge Velcy The erge elcy prcle s dened s The erge elcy depends nly n he nl nd he nl psns he prcle. Ths mens h prcle srs rm pn nd reurn bck he sme pn, s dsplcemen, nd s s erge elcy s

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

More information

Lecture 2 M/G/1 queues. M/G/1-queue

Lecture 2 M/G/1 queues. M/G/1-queue Lecure M/G/ queues M/G/-queue Posson arrval process Arbrary servce me dsrbuon Sngle server To deermne he sae of he sysem a me, we mus now The number of cusomers n he sysems N() Tme ha he cusomer currenly

More information

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s A g la di ou s F. L. 462 E l ec tr on ic D ev el op me nt A i ng er A.W.S. 371 C. A. M. A l ex an de r 236 A d mi ni st ra ti on R. H. (M rs ) A n dr ew s P. V. 326 O p ti ca l Tr an sm is si on A p ps

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

Motion. Part 2: Constant Acceleration. Acceleration. October Lab Physics. Ms. Levine 1. Acceleration. Acceleration. Units for Acceleration.

Motion. Part 2: Constant Acceleration. Acceleration. October Lab Physics. Ms. Levine 1. Acceleration. Acceleration. Units for Acceleration. Moion Accelerion Pr : Consn Accelerion Accelerion Accelerion Accelerion is he re of chnge of velociy. = v - vo = Δv Δ ccelerion = = v - vo chnge of velociy elpsed ime Accelerion is vecor, lhough in one-dimensionl

More information

Introduction. Voice Coil Motors. Introduction - Voice Coil Velocimeter Electromechanical Systems. F = Bli

Introduction. Voice Coil Motors. Introduction - Voice Coil Velocimeter Electromechanical Systems. F = Bli UNIVERSITY O TECHNOLOGY, SYDNEY ACULTY O ENGINEERING 4853 Elecroechncl Syses Voce Col Moors Topcs o cover:.. Mnec Crcus 3. EM n Voce Col 4. orce n Torque 5. Mhecl Moel 6. Perornce Voce cols re wely use

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

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

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon If we say wh one bass se, properes vary only because of changes n he coeffcens weghng each bass se funcon x = h< Ix > - hs s how we calculae

More information

An Improvement on Disc Separation of the Schur Complement and Bounds for Determinants of Diagonally Dominant Matrices

An Improvement on Disc Separation of the Schur Complement and Bounds for Determinants of Diagonally Dominant Matrices ISSN 746-7659, Egd, UK Jor of Iformo d Compg See Vo. 5, No. 3, 2, pp. 224-232 A Improveme o Ds Sepro of he Shr Compeme d Bods for Deerms of Dgoy Dom Mres Zhohog Hg, Tgzh Hg Shoo of Mhem Sees, Uversy of

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

Use 10 m/s 2 for the acceleration due to gravity.

Use 10 m/s 2 for the acceleration due to gravity. ANSWERS Prjecle mn s he ecrl sum w ndependen elces, hrznl cmpnen nd ercl cmpnen. The hrznl cmpnen elcy s cnsn hrughu he mn whle he ercl cmpnen elcy s dencl ree ll. The cul r nsnneus elcy ny pn lng he prblc

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

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC

Rank One Update And the Google Matrix by Al Bernstein Signal Science, LLC Introducton Rnk One Updte And the Google Mtrx y Al Bernsten Sgnl Scence, LLC www.sgnlscence.net here re two dfferent wys to perform mtrx multplctons. he frst uses dot product formulton nd the second uses

More information

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

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

More information

4.1 Schrödinger Equation in Spherical Coordinates

4.1 Schrödinger Equation in Spherical Coordinates Phs 34 Quu Mehs D 9 9 Mo./ Wed./ Thus /3 F./4 Mo., /7 Tues. / Wed., /9 F., /3 4.. -. Shodge Sphe: Sepo & gu (Q9.) 4..-.3 Shodge Sphe: gu & d(q9.) Copuo: Sphe Shodge s 4. Hdoge o (Q9.) 4.3 gu Moeu 4.4.-.

More information

1. Find a basis for the row space of each of the following matrices. Your basis should consist of rows of the original matrix.

1. Find a basis for the row space of each of the following matrices. Your basis should consist of rows of the original matrix. Mh 7 Exm - Prcice Prolem Solions. Find sis for he row spce of ech of he following mrices. Yor sis shold consis of rows of he originl mrix. 4 () 7 7 8 () Since we wn sis for he row spce consising of rows

More information

rank Additionally system of equation only independent atfect Gawp (A) possible ( Alb ) easily process form rang A. Proposition with Definition

rank Additionally system of equation only independent atfect Gawp (A) possible ( Alb ) easily process form rang A. Proposition with Definition Defiion nexivnol numer ler dependen rows mrix sid row Gwp elimion mehod does no fec h numer end process i possile esily red rng fc for mrix form der zz rn rnk wih m dcussion i holds rr o Proposiion ler

More information

Some Inequalities variations on a common theme Lecture I, UL 2007

Some Inequalities variations on a common theme Lecture I, UL 2007 Some Inequliies vriions on common heme Lecure I, UL 2007 Finbrr Hollnd, Deprmen of Mhemics, Universiy College Cork, fhollnd@uccie; July 2, 2007 Three Problems Problem Assume i, b i, c i, i =, 2, 3 re rel

More information

Advanced Machine Learning

Advanced Machine Learning Avne Mhne Lernng Lernng Grh Moes Mu kehoo ernng o unree GM Er Xng Leure 5 Augus 009 Reng: Er Xng Er Xng @ CMU 006009 Re: or Bs Assung he reers or eh CPD re goy neenen n noes re uy oserve hen he kehoo unon

More information

12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer

12d Model. Civil and Surveying Software. Drainage Analysis Module Detention/Retention Basins. Owen Thornton BE (Mech), 12d Model Programmer d Model Cvl and Surveyng Soware Dranage Analyss Module Deenon/Reenon Basns Owen Thornon BE (Mech), d Model Programmer owen.hornon@d.com 4 January 007 Revsed: 04 Aprl 007 9 February 008 (8Cp) Ths documen

More information

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X ECON 37: Ecoomercs Hypohess Tesg Iervl Esmo Wh we hve doe so fr s o udersd how we c ob esmors of ecoomcs reloshp we wsh o sudy. The queso s how comforble re we wh our esmors? We frs exme how o produce

More information

Rotations.

Rotations. oons j.lbb@phscs.o.c.uk To s summ Fmes of efeence Invnce une nsfomons oon of wve funcon: -funcons Eule s ngles Emple: e e - - Angul momenum s oon geneo Genec nslons n Noehe s heoem Fmes of efeence Conse

More information

September 20 Homework Solutions

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

More information

AN A(α)-STABLE METHOD FOR SOLVING INITIAL VALUE PROBLEMS OF ORDINARY DIFFERENTIAL EQUATIONS

AN A(α)-STABLE METHOD FOR SOLVING INITIAL VALUE PROBLEMS OF ORDINARY DIFFERENTIAL EQUATIONS Advances n Derenal Eqaons and Conrol Processes 4 Pshpa Pblshng Hose, Allahabad, Inda Avalable onlne a hp://pphm.com/ornals/adecp.hm Volme, Nmber, 4, Pages AN A(α)-STABLE METHOD FOR SOLVING INITIAL VALUE

More information

Neural Network Introduction. Hung-yi Lee

Neural Network Introduction. Hung-yi Lee Neu Neto Intoducton Hung- ee Reve: Supevsed enng Mode Hpothess Functon Set f, f : : (e) Tnng: Pc the est Functon f * Best Functon f * Testng: f Tnng Dt : functon nput : functon output, ˆ,, ˆ, Neu Neto

More information

Existence of Periodic Solution for a Non-Autonomous Stage-Structured Predator-Prey System with Impulsive Effects

Existence of Periodic Solution for a Non-Autonomous Stage-Structured Predator-Prey System with Impulsive Effects Appled ahemacs 55-6 do:.6/am.. Pblshed Onlne arch (hp://www.scrp.org/jornal/am) Exsence o Perodc Solon or a Non-Aonomos Sage-Srcred Predaor-Prey Sysem wh Implsve Eecs Absrac eng W Zolang Xong Ypng Deng

More information

Contraction Mapping Principle Approach to Differential Equations

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

More information

An Optimization Model for Empty Container Reposition under Uncertainty

An Optimization Model for Empty Container Reposition under Uncertainty n Omzon Mode o Emy onne Reoson nde neny eodo be n Demen o Mnemen nd enooy QM nd ene de Reee s es nsos Moné nd Mssmo D Fneso Demen o Lnd Enneen nesy o Iy o Zdds Demen o Lnd Enneen nesy o Iy Inodon. onne

More information

I I M O I S K J H G. b gb g. Chapter 8. Problem Solutions. Semiconductor Physics and Devices: Basic Principles, 3 rd edition Chapter 8

I I M O I S K J H G. b gb g. Chapter 8. Problem Solutions. Semiconductor Physics and Devices: Basic Principles, 3 rd edition Chapter 8 emcouc hyscs evces: Bsc rcles, r eo Cher 8 oluos ul rolem oluos Cher 8 rolem oluos 8. he fwr s e ex f The e ex f e e f ex () () f f f f l G e f f ex f 59.9 m 60 m 0 9. m m 8. e ex we c wre hs s e ex h

More information

f t f a f x dx By Lin McMullin f x dx= f b f a. 2

f t f a f x dx By Lin McMullin f x dx= f b f a. 2 Accumulion: Thoughs On () By Lin McMullin f f f d = + The gols of he AP* Clculus progrm include he semen, Sudens should undersnd he definie inegrl s he ne ccumulion of chnge. 1 The Topicl Ouline includes

More information

THE POLYNOMIAL TENSOR INTERPOLATION

THE POLYNOMIAL TENSOR INTERPOLATION Pease ce hs arce as: Grzegorz Berna, Ana Ceo, The oynoma ensor neroaon, Scenfc Research of he Insue of Mahemacs and Comuer Scence, 28, oume 7, Issue, ages 5-. The webse: h://www.amcm.cz./ Scenfc Research

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

Chapter Simpson s 1/3 Rule of Integration. ( x)

Chapter Simpson s 1/3 Rule of Integration. ( x) Cper 7. Smpso s / Rule o Iegro Aer redg s per, you sould e le o. derve e ormul or Smpso s / rule o egro,. use Smpso s / rule o solve egrls,. develop e ormul or mulple-segme Smpso s / rule o egro,. use

More information