Zjavka: Recognition of Generalized Patterns by a Differential Polynomial eural etwork

Size: px
Start display at page:

Download "Zjavka: Recognition of Generalized Patterns by a Differential Polynomial eural etwork"

Transcription

1 ETASR - Egeerg Techolog & Appled Scece Reserch Vol. o. 6-6 Recogto o Geerlzed Ptters Deretl Polol Neurl Netor Ldslv Zjv cult o Mgeet Scece d Iortcs Uverst o Žl Žl Slov lzjv@gl.co Astrct A lot o proles volve uo dt reltos detcto o hch c serve s geerlzto o ther qultes. Reltve vlues o vrles re ppled ths cse d ot the solute vlues hch c etter e use o dt propertes de rge o the vldt. Ths reseles ore to the uctolt o the r hch sees to geerlze reltos o vrles too th coo ptter clsscto. Deretl polol eurl etor s e tpe o eurl etor desged the uthor hch costructs d pprotes uo deretl equto o depedet vrles usg specl tpe o root ult-pretrc polols. It cretes rctol prtl deretl ters descrg utul dervtve chges o soe vrles lese the deretl equto does. Prtculr polols ctch reltos o gve cotos o put vrles. Ths tpe o detcto s ot sed o hole-ptter slrt ut ol to the lered hdde geerlzed reltos o vrles. Keords - polol eurl etor; depedece o vrles detcto; deretl equto pproto; rtol tegrl ucto I. INTRODUCTION The prcpl dsdvtge o the rtcl eurl etor (ANN detcto geerl s the dslt o put ptter geerlzto. ANNs c ler to clss put ptters ut utlze ol the solute vlues o vrles. Hoever the ltter der sgctl hle ther reltos e the se. Tht s h ANNs re le to correctl recogze ol slr or coplete ptters copred to the tr set. I the put cosdered s e.g. shpe oved or szed the put tr the eurl etor detcto ll l. A pproch to loo t the put vector o vrles ot s ptter ut s depedet oud pot set o N-desol spce could e ttepted. A eurl etor hch ould e le to ler d det uo dt reltos s to cot ultpretrc polol uctos to ctch prtl depedece o gve puts. Its respose ould e the se to ll ptters (sets hch vrles re perored th the tred depedece regrdless o the ctul vlues [9]. Bologcl eurl cell sees to ppl slr prcple. Its dedrtes collect electrcl sgls cog ro other euros. But ule the rtcl euro soe o the sgls lred terct sgle rches (dedrtes o eurl cell (see gure lese the ultpled vrles o ult-pretrc polol do. Preters o polol ters c represet the sopss o the cell dedrtes. These eghted cotos re sued the od cell d trsored to reltve vlues usg te-deled dc perodc ctvto uctos (the ctvted eurl cell geertes seres o te-deled output pulses respose to ts put sgls. Ao psses electrcl pulse sgls o to dedrtes o other eurl or eector cells []. The perod o ths ucto depeds o soe put vrles d sees to represet the dervtve prt o prtl ter o deretl equto coposto. Deretl polol eurl etor (D-PNN costructs d tres to pprote uo deretl equto descrg reltos o put vrles tht re ot etrel ptters. It ors ts output s geerlzto o put ptters slr to the oes utlzed the hu r. It cretes structurl odel o uo reltoshps o put vrles descrpto. D-PNN s sed o GMDH (Group Method o Dt Hdlg polol eurl etor hch s creted the Ur scetst Alese Ivheo 968 he the c-propgto techque s ot o et. He ttepted to decopose the coplet o process to spler reltoshps ech descred lo order -vrle polol processg ucto o sgle euro []. g.. A ologcl eurl cell

2 ETASR - Egeerg Techolog & Appled Scece Reserch Vol. o II. DIERENTIAL POLYNOMIAL NEURAL NETWORK The sc de o the D-PNN s to crete d pprote deretl equto (DE ( hch s ot o dvce [] th specl tpe o root (poer rctol ultpretrc polols (5. Coto degree (5 / / euros u c j j j u u u( - serched ucto o ll put vrles B( C(c c - preters ( Π polol Bloc output Eteded euros ourer s ethod o prtl DE soluto serches the soluto or o the product o uctos o hch t lest depeds ol o vrle. A prtl dervto o ucto z( o put vrles c e epressed ( []. z( ( ( z ( Eleetr ethods o deretl equto soluto epress the soluto specl eleetr uctos polols (e.g. Bessel s uctos ourer s poer seres. Nuercl tegrto o deretl equtos s sed o ther pproto through: rtol tegrl uctos trgooetrc seres The st d ore sple hs ee selected usg the ethod o tegrl logues hch replces thetcl opertors d sols DE the rto o correspodg vrles. Dervtves re replced the tegrl logues.e. dervtve opertors re reoved d sulteousl ll opertors re replced slrl or proporto rs equtos ll vectors re replced ther solute vlues. Desol ters re dvded soe others hch results serched o-desol leess crteros [5]. ( ( (5 ( coto degree o -put vrle polol o uertor coto degree o deotor (< g.. A loc o deretl euros Ech ler o the D-PNN cossts o locs hch cot dervtve euros oe or ech rctol polol (5 deg the prtl dervtve depedet chge o soe put vrles. A loc lso cots ddtol eteded euros (EN hch or copoud uctos (5 pplg prevous ler loc outputs. Ech loc cots sgle polol (thout dervtve prt hch ors ts output etrce to the et hdde ler (gure.. Neuros do t ect the loc output ut re ppled ol or the totl output clculto (DE coposto. Ech euro hs vectors o djustle preters d ech loc cots vector o djustle preters o the output polol. The root uctos o deotors (5 re loer th ccordg to the coto degree hch te the polols o euros to copetet poer degree. The c e replced poer uctos o deotors. Iputs o costt coto degree ( org prtculr cotos o vrles eter ech loc here the re susttuted to polols (gure.. It s ecessr to djust ot ol the polol preters ut lso the D-PNN s structure. Ths es soe euros ters o role o the DE re to e let out. p j q j Y.. t r u v t eghts o ters The rctol polols (5 hch c descre prtl depedece o -put vrles o ech euro re ppled s ters o the DE (6 coposto. The prtl crete uo ult-pretrc o-ler ucto hch codes reltos o put vrles. The uertor o (5 s polol o coplete -put coto degree o sgle euro d relzes e ucto z o orul (. The deotor o (5 s dervtve prt hch gves prtl utul chge o soe euro put vrles d ts polol coto degree s less the. It rose ro the prtl dervto o the coplete -vrle polol copetet vrle(s. (6 g.. Deretl polol eurl etor

3 ETASR - Egeerg Techolog & Appled Scece Reserch Vol. o III. IDENTIICATION O SIMPLE LINEAR DEPENDENCIES Cosder ver sple depedece o -put vrles hch ultplct s costt (e.g.. D-PNN ll cot ol loc o polol euros ((8 s ters o DE (gure.. As the put vrles do t chge costtl t s ecessr to dd oth ters (rctol polol o dervtve vrle d the DE (loc. D-PNN ll ler ths relto esl ccordg to sples o the trg dt set es o geetc d evoluto lgorth (GA []. ( (8 Cosder ore coplcted ler depedece here vrles deped o rd. or eple su o the rst vrles equls the rd vrle (. The coplete DE (or dervtves d -cotos o loc cossts o 6 ters (euros ut ol o the ll e eough or dervtve ters (9 ( (. I other ters (euros re dded the D-PNN ll or ss (see gure 5. To-vrle coto polols o uertors ((8 c e lso ppled hch could prove the D-PNN uctolt d crese the uer o the DE ters. Ths - vrle depedece s descred ore coplcted epoetl uctos. The D-PNN s ell s chrged the possle -sded depedet chge o put vrles. or eple 9 s the se su s 9. The prcpl phse o ts djustet resdes eltg o soe euros ( ters o the DE. g.. Idetcto o costt quotet o vrles ( g. 5. Idetcto o the su depedece (9 ( ( Mult-lered D-PNN cretes copoud polol uctos. M epoetl uctos o hgher lers crr soe secodr uctos o prevous lers descrg the prtl reltos o ts vrles. ro thetcl pot o ve the st hdde ler ors the er uctos hch susttute the put vrles o d hdde ler euro d loc polols - the outer uctos. Provded ths ssupto e re le to clculte the prtl dervtves o copoud uctos vrles o prevous lers s DE ters ( ro the er uctos ( o outer ucto (. These copoud DE ters re ored s products o prtl dervtves o d er uctos (5 [6]. ( ( X ( ( ( (φ (X φ (X φ (X (. ( X ( ( φ (5 g. 6. Idetcto o the -vrle depedece th -coto locs / Bloc output Neuro Neuro ( (8 Bloc output Neuro Neuro Neuro (9 ( (

4 ETASR - Egeerg Techolog & Appled Scece Reserch Vol. o. 6- Ech loc o the D-PNN ors prtl DE ters utlzg ts sc d eteded euros. Sgle djustle polol (P gure 6. thout dervtve prt cretes the loc output (pplg the et hdde ler ut the euros re ppled ol or the totl DE coposto. The locs o the d d the ollog hdde lers crete copoud ters (CT o the DE usg ther ddtol eteded euros outputs d puts o c coected locs o prevous lers. Cosder or stce the st loc o the lst hdde ler hch tes ts o euros s sc ters (6 o the DE (6. Susequetl t cretes eteded ters o the d (prevous hdde ler vrles usg reverse output polols d puts o oud locs. It cretes rctol copoud ters o the DE or dervtve put vrles o prevous hdde ler usg dervtos o copoud d er uctos (. As couples o vrles o the er uctos φ ( d φ ( der ro ech other ther prtl dervtos re d so the su (5 ll cosst ol o ter. ( ( ( ( ( c c ( ( ( d d ( ( (6 ( (8 ( The prevous ler loc reverse outputs re used to crete ecessr prtl dervtos o the outer d er uctos (o polols o deretl euros (. Lese copoud ters c e creted or the st hdde ler (8. The led locs org 8 ters o the DE ere ttched to the presetl djusted loc. Ths c e perored ell recursve lgorth. It s ot ever ter tht s used the coplete DE; soe o the ere ecessrl let out. Ths dctes or the euros o locs d s ese to use the s gees o GA. Preters o polols re represeted rel uers. A chroosoe s sequece o ther vlues hch c e es utted. The D-PNN s totl output Y s the su o ll ctve prtl DE ter vlues ccordg to (9 hch the preset ctve out c e ult. Y totl out o DE ters (9 It c e see tht the -vrle D-PNN (gure 6. susttll cossts o overlg edge etors (WN ech gog c out ro the locs o the lst hdde ler d grdull ttchg to the dervtve vrles o prevous lers. The D-PNN o the depedet put vrles usg - coto locs ll hve totll 6 locs o ll put coto couples the st hdde ler. The uer o cotos or ll vrles creses eorousl ech et hdde ler. Ths could e solved pplg WNs s ol soe o the locs re creted d used. The totl out o D-PNN s hdde lers could equl t lest to the uer o put vrles (.e. s t ust e le to crete ech coto o hch d to rech c ll dervtve vrles o the st ler. So WNs o the st hdde ler ll volve. rdo locs cosequetl the d ler ll cot. locs etc. Ths the uer o ll WN locs decreses ech et hdde ler utl s reched just loc. D-PNN ll hve severl overlg WNs prtl the lers g. Soe WN lers overl ech other d so the locs c e used severl tes deret WNs (gure.. The locs o the d d ollog hdde lers c e recoected d ths could copeste ssg coto locs. The coectos o the coplete st hdde ler locs re ed. Lese the prevous -vrle D-PNN tpe does t c costruct the prtl rctol ters o the DE ro c-coected locs o prevous lers. All WN locs ttch c grdull the dervtve vrles o prevous lers. The serchg spce cots gret out o locl error solutos hch GA c sh esl. Ths prole s cused lot o possle cotos o loc puts d coposed DE ters (ol soe o the e eploed hch selecto s crtcl phse o the D-PNN s costructo esdes the sulteous preter djustet []. g.. Wedge etors o the -vrle -coto D-PNN The D-PNN o the 6 depedet put vrles usg - coto locs ll hve totll 5 locs o ll put coto couples the st hdde ler d 6 hdde lers. Hoever eperet th rght trgles (gure 9 d gure. t could e sucet th hdde lers g ecuse there s the u o -vrle depedece to det. IV... DE EXPERIMENTS -vrle D-PNN s le to det ro/colu or dgol depedece o chess peces (gure 8.. Iput vector s ored ther postos (ro colu. I the hte roo checs the lc shop ther or postos equl d ths c D-PNN ler to det. Aother relto occurs the lc shop checs the hte roo the su or derece o ther d -postos re equl A A B B or A A B B. Tle d Tle sho etor resposes to depedet d

5 ETASR - Egeerg Techolog & Appled Scece Reserch Vol. o. 6- depedet vrles o put vectors. Trg dt set c cosst o ollog 5 dt sples d -postos o the chess peces (the chessord s elrged [9]: {} {65} {} {68} {558} {5} 5 6 posto the put tr (gure 9.. Iput vector o the D- PNN s ored (ro colu coordtes o the trgle pees A B C. The depedece o pots A C s dgol A B vertcl d B C horzotl. As there re sulteousl occurred tpes o pot reltos t s ecessr to crese the uer o locs o D-PNN s hdde lers. Trg dt set c cosst o ollog 5 dt sples rght equl-sed trgles : {69} {} {555} {} {555555} Testg rdo rght trgles ust eep the pees A B C depedet to e correctl recogzed D-PNN. Tle shos resposes o tred etor to depedet rght trgles. Tle. pples ol vertcl deortos ( d o rght trgles C pees (g.. do to e sho trspret seprtg ple detchg the reltve trgles. 5 6 g. 8. Reltos o chess peces TABLE I. RESPONSES TO RANDOM INPUT VECTORS WITH DEPENDENT VARIABLES Iput vector Output TABLE II. RESPONSES TO RANDOM INDEPENDENT INPUT VECTORS O VARIABLES Iput vector Output Iput vector Output ( ( < > < 5. 5 > < > < 8.9 > < > < > < 8.65 > < >.9 5 < > 5.9 g. 9. Depedet rght equl-sded trgle shpes A seprtg ple could e otced detched ro the reltve clsses hch hve the se chrcterstc ( the su o the st couple s less the t should e the output s less the the desred roud d other hd roud. D-PNN c e tred ol th sll put-output dt sples (lese the GMDH polol eurl etor does to ler depedece [8]. 6-vrle D-PNN c ler to det (geerlze chgele shpe (e.g. trgle regrdless o ts sze or g.. Idepedet deored rght trgles pees A d C

6 ETASR - Egeerg Techolog & Appled Scece Reserch Vol. o. 6- TABLE III. RESPONSES TO RANDOM INPUT VECTORS WITH 6 DEPENDENT VARIABLES (RIGHT TRIANGLES Iput vector (A A B B C C Output TABLE IV. RESPONSES TO RANDOM INDEPENDENT INPUT VECTORS O 6 VARIABLES (DEORMED RIGHT TRIANGLES IN C APEXES Iput vector (A B C Output Iput vector (A B C Output V. DISCUSSION Ol ler depedeces o vrles hve ee ssued or splct the eples preseted. I there s occurrece o o ler depedece o the put dt the squre poer epoet vrles ould eted coto polols o euros d ppled lso s copetet dervtve ters (. The deotors o (( result ro the prtl dervtves o the coplete DE ter polols o uertors. The root squre (or poer uctos re lel ot volved to rctos ( the dereces o vlues o put vrles re ot too g ( cse rel dt odel s occurred preseted eples. ( ( ( j 5 5 ( ( ( Accordg to (-(5 t s possle to dee hgher degree prtl dervtos o -vrle copoud ucto ((uv ( [6]. As the vrles o the D-PNN s er uctos uφ( d ψ( re deret the d rd d 5 th ters o eq. ( re (s the prtl dervto o ψ s. Lese the ters o ( d (5 do [6]. ( ( u v [ ( ψ ( ] uφ( vψ( ( ψ ψ ψ ( v v v ψ ψ ψ ( v v ψ ψ u u v ψ ψ ψ v v v (5 A rel dt eple ght solve the ether orecst sed o soe tred dt reltos hch re used or clcultg the et stte o sste. Let s te severl tpes o vrles (e.g. pressure dp teperture prtl descrg sttes o ths ver cople sste. The put vector o the D-PNN s ored vlues o these vrles deed tr coordtes o eteorologcl p. The trg dt set cludes dete sttes o te tervl d desred etor outputs. The output could r the ether orecst s rlls cloud sushe. There c turll rse possle trset sttes (e.g... The output s coputed or loclt o the p d could lso predct the tospherc pressure or other qutt. VI. CONCLUSION Artcl eurl etors geerl respod to relted ptters th slr output. The det put ptters o the ses o ther reltoshp. Lese the detcto o uo depedeces o the dt vrles could lso e cosdered. Ths could e regrded s ptter o strcto slr to tht utlzed the hu r hch pples the pproto th te-deled perodc ctvto uctos o ologcl euros hgh dc sste o ehvor. D- PNN s e tpe o eurl etor hch perors detcto sed o uo geerlzed reltos o put vrles. D-PNN ors ts uctol output s coposto o deretl equto ters (hch descre sste o depedet vrles ro rtol tegrl uctos. The prole o the ult-lered D-PNN costructo resde cretes ever prtl coto ter or coplete DE utlzg soe ed lo coto degrees ( hle the out o vrles s s rule hgher. REERENCES [] Ľ. Beňušová Neuro d r. Cogtve sceces Cllgr Brtslv ( Slov. [] A.G. Ivheo Polol theor o cople sstes IEEE Trsctos o sstes Vol. SMC- No. pp [] J. Hroec Deretl equtos II. SAV Brtslv 958 ( Slov. [] R. Rchovsý J. Výorá Prtl deretl equtos d soe o ther solutos Pul. SNTL Prh 9 ( Czech. [5] J. Kueš O. Vvroch V. rt Prcples o odellg SNTL Prh 989 ( Czech. [6] I. Kluváe L. Mší M. Švec Mtetcs I. II. SNTL Brtslv 966 ( Slov. [] S. Ds A. Arh A. Kor Prtcle sr ptzto d deretl evoluto lgorths: Techcl slss pplctos d hrdzto perspectves Coputer d Iorto Scece Vol. 8 pp [8] B. B. Msr S. Dehur P.K. Dsh G. Pd A reduced d coprehesle polol eurl etor or clsscto Ptter recogto letters Vol. 9 No. pp [9] L. Zjv Geerlzto o ptters detcto th polol eurl etor Jourl o Electrcl Egeerg Vol. 6 No. pp. - [] L. Zjv Costructo d djustet o deretl polol eurl etor Jourl o Egeerg d Coputer Iovtos Vol. No. pp. -5

CURVE FITTING LEAST SQUARES METHOD

CURVE FITTING LEAST SQUARES METHOD Nuercl Alss for Egeers Ger Jord Uverst CURVE FITTING Although, the for of fucto represetg phscl sste s kow, the fucto tself ot be kow. Therefore, t s frequetl desred to ft curve to set of dt pots the ssued

More information

Review of Linear Algebra

Review of Linear Algebra PGE 30: Forulto d Soluto Geosstes Egeerg Dr. Blhoff Sprg 0 Revew of Ler Alger Chpter 7 of Nuercl Methods wth MATLAB, Gerld Recktewld Vector s ordered set of rel (or cople) uers rrged s row or colu sclr

More information

APPLICATION OF THE CHEBYSHEV POLYNOMIALS TO APPROXIMATION AND CONSTRUCTION OF MAP PROJECTIONS

APPLICATION OF THE CHEBYSHEV POLYNOMIALS TO APPROXIMATION AND CONSTRUCTION OF MAP PROJECTIONS APPLICATION OF THE CHEBYSHEV POLYNOMIALS TO APPROXIMATION AND CONSTRUCTION OF MAP PROJECTIONS Pweł Pędzch Jerzy Blcerz Wrsw Uversty of Techology Fculty of Geodesy d Crtogrphy Astrct Usully to pproto of

More information

More Regression Lecture Notes CE 311K - McKinney Introduction to Computer Methods Department of Civil Engineering The University of Texas at Austin

More Regression Lecture Notes CE 311K - McKinney Introduction to Computer Methods Department of Civil Engineering The University of Texas at Austin More Regresso Lecture Notes CE K - McKe Itroducto to Coputer Methods Deprtet of Cvl Egeerg The Uverst of Tes t Aust Polol Regresso Prevousl, we ft strght le to os dt (, ), (, ), (, ) usg the lest-squres

More information

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is Mth Sprg 08 L Approxmtg Dete Itegrls I Itroducto We hve studed severl methods tht llow us to d the exct vlues o dete tegrls However, there re some cses whch t s ot possle to evlute dete tegrl exctly I

More information

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini DATA FITTING Itesve Computto 3/4 Als Mss Dt fttg Dt fttg cocers the problem of fttg dscrete dt to obt termedte estmtes. There re two geerl pproches two curve fttg: Iterpolto Dt s ver precse. The strteg

More information

Statistical Modeling and Analysis of the Correlation between the Gross Domestic Product per Capita and the Life Expectancy

Statistical Modeling and Analysis of the Correlation between the Gross Domestic Product per Capita and the Life Expectancy Als of Dure de Jos Uerst of Glt Fsccle. Ecoocs d Appled fortcs Yers XX o /5 N-L 584-49 N-Ole 44-44X www.e.fe.ugl.ro ttstcl Mode d Alss of the Correlto etwee the Gross Doestc Product per Cpt d the Lfe Epectc

More information

6.6 Moments and Centers of Mass

6.6 Moments and Centers of Mass th 8 www.tetodre.co 6.6 oets d Ceters of ss Our ojectve here s to fd the pot P o whch th plte of gve shpe lces horzotll. Ths pot s clled the ceter of ss ( or ceter of grvt ) of the plte.. We frst cosder

More information

CS321. Numerical Analysis

CS321. Numerical Analysis CS3 Nuercl Alss Lecture 7 Lest Sures d Curve Fttg Professor Ju Zhg Deprtet of Coputer Scece Uverst of Ketuc Legto KY 456 633 Deceer 4 Method of Lest Sures Coputer ded dt collectos hve produced treedous

More information

An Alternative Method to Find the Solution of Zero One Integer Linear Fractional Programming Problem with the Help of -Matrix

An Alternative Method to Find the Solution of Zero One Integer Linear Fractional Programming Problem with the Help of -Matrix Itertol Jourl of Scetfc d Reserch Pulctos, Volue 3, Issue 6, Jue 3 ISSN 5-353 A Altertve Method to Fd the Soluto of Zero Oe Iteger Ler Frctol Progrg Prole wth the Help of -Mtr VSeeregsy *, DrKJeyr ** *

More information

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ]

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ] Atervtves The Itegrl Atervtves Ojectve: Use efte tegrl otto for tervtves. Use sc tegrto rules to f tervtves. Aother mportt questo clculus s gve ervtve f the fucto tht t cme from. Ths s the process kow

More information

The z-transform. LTI System description. Prof. Siripong Potisuk

The z-transform. LTI System description. Prof. Siripong Potisuk The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put

More information

The Derivation of Implicit Second Derivative Method for Solving Second-Order Stiff Ordinary Differential Equations Odes.

The Derivation of Implicit Second Derivative Method for Solving Second-Order Stiff Ordinary Differential Equations Odes. IOSR Jourl o Mtetcs (IOSR-JM) e-issn: - p-issn: 9-6X. Volue Issue Ver. I (Mr. - Apr. ) PP - www.osrourls.org Te Dervto o Iplct Secod Dervtve Metod or Solvg Secod-Order St Ordr Deretl Equtos Odes. Y. Skwe

More information

International Journal of Scientific and Research Publications, Volume 3, Issue 5, May ISSN

International Journal of Scientific and Research Publications, Volume 3, Issue 5, May ISSN Itertol Jourl of Scetfc d Reserch Pulctos, Volue 3, Issue 5, My 13 1 A Effcet Method for Esy Coputto y Usg - Mtr y Cosderg the Iteger Vlues for Solvg Iteger Ler Frctol Progrg Proles VSeeregsy *, DrKJeyr

More information

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants Rochester Isttute of echology RI Scholr Wors Artcles 8-00 bocc d ucs Nubers s rdgol trx Deterts Nth D. Chll Est Kod Copy Drre Nry Rochester Isttute of echology ollow ths d ddtol wors t: http://scholrwors.rt.edu/rtcle

More information

A Comparison of Chebyshev polynomials and Legendre polynomials in order to solving Fredholm integral equations

A Comparison of Chebyshev polynomials and Legendre polynomials in order to solving Fredholm integral equations tertol Jourl o Scetc Reserch ulctos Volue 6 ssue 3 Mrch 6 35 SSN 5-353 A Coprso o Cheshev polols Leere polols orer to solv Frehol terl equtos Mlr Astrct- ths reserch we use the uercl soluto etho tht s

More information

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ]

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ] Are d the Defte Itegrl 1 Are uder Curve We wt to fd the re uder f (x) o [, ] y f (x) x The Prtto We eg y prttog the tervl [, ] to smller su-tervls x 0 x 1 x x - x -1 x 1 The Bsc Ide We the crete rectgles

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I Uversty o Hw ICS: Dscrete Mthemtcs or Computer Scece I Dept. Iormto & Computer Sc., Uversty o Hw J Stelovsy bsed o sldes by Dr. Be d Dr. Stll Orgls by Dr. M. P. Fr d Dr. J.L. Gross Provded by McGrw-Hll

More information

A New Efficient Approach to Solve Multi-Objective Transportation Problem in the Fuzzy Environment (Product approach)

A New Efficient Approach to Solve Multi-Objective Transportation Problem in the Fuzzy Environment (Product approach) Itertol Jourl of Appled Egeerg Reserch IN 097-6 Volue, Nuer 8 (08) pp 660-66 Reserch Id Pulctos http://wwwrpulctoco A New Effcet Approch to olve Mult-Oectve Trsportto Prole the Fuzzy Evroet (Product pproch)

More information

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases Itertol Jourl of Advced Reserch Physcl Scece (IJARPS) Volume, Issue 5, September 204, PP 6-0 ISSN 2349-7874 (Prt) & ISSN 2349-7882 (Ole) www.rcourls.org Alytcl Approch for the Soluto of Thermodymc Idettes

More information

MTH 146 Class 7 Notes

MTH 146 Class 7 Notes 7.7- Approxmte Itegrto Motvto: MTH 46 Clss 7 Notes I secto 7.5 we lered tht some defte tegrls, lke x e dx, cot e wrtte terms of elemetry fuctos. So, good questo to sk would e: How c oe clculte somethg

More information

SUMMARY OF THE ZETA REGULARIZATION METHOD APPLIED TO THE CALCULATION OF DIVERGENT SERIES

SUMMARY OF THE ZETA REGULARIZATION METHOD APPLIED TO THE CALCULATION OF DIVERGENT SERIES SUMMARY OF THE ZETA REGULARIZATION METHOD APPLIED TO THE CALCULATION OF DIVERGENT SERIES AND DIVERGENT INTEGRALS s d s Jose Jver Grc Moret Grdute studet of Physcs t the UPV/EHU (Uversty of Bsque coutry

More information

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES

SUM PROPERTIES FOR THE K-LUCAS NUMBERS WITH ARITHMETIC INDEXES Avlble ole t http://sc.org J. Mth. Comput. Sc. 4 (04) No. 05-7 ISSN: 97-507 SUM PROPERTIES OR THE K-UCAS NUMBERS WITH ARITHMETIC INDEXES BIJENDRA SINGH POOJA BHADOURIA AND OMPRAKASH SIKHWA * School of

More information

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11:

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11: Soo Kg Lm 1.0 Nested Fctorl Desg... 1.1 Two-Fctor Nested Desg... 1.1.1 Alss of Vrce... Exmple 1... 5 1.1. Stggered Nested Desg for Equlzg Degree of Freedom... 7 1.1. Three-Fctor Nested Desg... 8 1.1..1

More information

CS321. Introduction to Numerical Methods

CS321. Introduction to Numerical Methods CS Itroducto to Numercl Metods Lecture Revew Proessor Ju Zg Deprtmet o Computer Scece Uversty o Ketucky Legto, KY 6 6 Mrc 7, Number Coverso A geerl umber sould be coverted teger prt d rctol prt seprtely

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 Mtr Trsformtos usg Egevectors September 8, Mtr Trsformtos Usg Egevectors Lrry Cretto Mechcl Egeerg A Semr Egeerg Alyss September 8, Outle Revew lst lecture Trsformtos wth mtr of egevectors: = - A ermt

More information

CHAPTER 6 CURVE FITTINGS

CHAPTER 6 CURVE FITTINGS CHAPTER 6 CURVE FITTINGS Chpter 6 : TOPIC COVERS CURVE FITTINGS Lest-Squre Regresso - Ler Regresso - Poloml Regresso Iterpolto - Newto s Dvded-Derece Iterpoltg Polomls - Lgrge Iterpoltg Polomls - Sple

More information

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions HK Km Slghtly moded //9 /8/6 Frstly wrtte t Mrch 5 Itertve Methods er Systems: Guss-Sedel Noler Systems Cse Study: Chemcl Rectos Itertve or ppromte methods or systems o equtos cosst o guessg vlue d the

More information

Mathematically, integration is just finding the area under a curve from one point to another. It is b

Mathematically, integration is just finding the area under a curve from one point to another. It is b Numerl Metods or Eg [ENGR 9] [Lyes KADEM 7] CHAPTER VI Numerl Itegrto Tops - Rem sums - Trpezodl rule - Smpso s rule - Rrdso s etrpolto - Guss qudrture rule Mtemtlly, tegrto s just dg te re uder urve rom

More information

On Solution of Min-Max Composition Fuzzy Relational Equation

On Solution of Min-Max Composition Fuzzy Relational Equation U-Sl Scece Jourl Vol.4()7 O Soluto of M-Mx Coposto Fuzzy eltol Equto N.M. N* Dte of cceptce /5/7 Abstrct I ths pper, M-Mx coposto fuzzy relto equto re studed. hs study s geerlzto of the works of Ohsto

More information

NUMERICAL SOLUTIONS OF SOME KINDS OF FRACTIONAL DIFFERENTIAL EQUATIONS

NUMERICAL SOLUTIONS OF SOME KINDS OF FRACTIONAL DIFFERENTIAL EQUATIONS Jourl of Al-Nhr Uersty Vol.1 (), Deceber, 009, pp.13-17 Scece NUMERICAL SOLUTIONS OF SOME KINDS OF FRACTIONAL DIFFERENTIAL EQUATIONS L. N. M. Tfq I. I. Gorl Deprtet of Mthetcs, Ib Al Hth College Eucto,

More information

MULTI-CRITERIA OPTIMIZATION BASED ON THE REGRESSION EQUATION SYSTEMS IDENTIFICATION

MULTI-CRITERIA OPTIMIZATION BASED ON THE REGRESSION EQUATION SYSTEMS IDENTIFICATION Mthetcl Modelg MUTI-CRITERIA OPTIMIZATION BASED ON THE REGRESSION EQUATION SYSTEMS IDENTIFICATION A.P. Koteo D.A. Pshe Sr Ntol Reserch Uverst Sr Russ Sr Stte Techcl Uverst Sr Russ Astrct. Cosder the prole

More information

Differentiation and Numerical Integral of the Cubic Spline Interpolation

Differentiation and Numerical Integral of the Cubic Spline Interpolation JOURNAL OF COMPUTER VOL. NO. OCTOBER 7 Deretto d Nuercl Itegrl o te Cuc ple Iterpolto g Go cool o Coputer cece d Tecolog Jgsu Uverst o cece d Tecolog Zejg C El: go_sg@otl.co Zue Zg d Cuge Co Ke Lortor

More information

Section 7.2 Two-way ANOVA with random effect(s)

Section 7.2 Two-way ANOVA with random effect(s) Secto 7. Two-wy ANOVA wth rdom effect(s) 1 1. Model wth Two Rdom ffects The fctors hgher-wy ANOVAs c g e cosdered fxed or rdom depedg o the cotext of the study. or ech fctor: Are the levels of tht fctor

More information

Keywords: Heptic non-homogeneous equation, Pyramidal numbers, Pronic numbers, fourth dimensional figurate numbers.

Keywords: Heptic non-homogeneous equation, Pyramidal numbers, Pronic numbers, fourth dimensional figurate numbers. [Gol 5: M 0] ISSN: 77-9655 IJEST INTENTIONL JOUNL OF ENGINEEING SCIENCES & ESECH TECHNOLOGY O the Hetc No-Hoogeeous Euto th Four Ukos z 6 0 M..Gol * G.Suth S.Vdhlksh * Dertet of MthetcsShrt Idr Gdh CollegeTrch

More information

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM S. Res. Chem. Commu.: (3 8-88 ISSN 77-669 GENERLIZED OPERTIONL RELTIONS ND PROPERTIES OF FRCTIONL NKEL TRNSFORM R. D. TYWDE *. S. GUDDE d V. N. MLLE b Pro. Rm Meghe Isttute o Teholog & Reserh Bder MRVTI

More information

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek Optmlt of Strteges for Collpsg Expe Rom Vrles Smple Rom Smple E Stek troucto We revew the propertes of prectors of ler comtos of rom vrles se o rom vrles su-spce of the orgl rom vrles prtculr, we ttempt

More information

The linear system. The problem: solve

The linear system. The problem: solve The ler syste The prole: solve Suppose A s vertle, the there ests uue soluto How to effetly opute the soluto uerlly??? A A A evew of dret ethods Guss elto wth pvotg Meory ost: O^ Coputtol ost: O^ C oly

More information

Algebra 2 Important Things to Know Chapters bx c can be factored into... y x 5x. 2 8x. x = a then the solutions to the equation are given by

Algebra 2 Important Things to Know Chapters bx c can be factored into... y x 5x. 2 8x. x = a then the solutions to the equation are given by Alger Iportt Thigs to Kow Chpters 8. Chpter - Qudrtic fuctios: The stdrd for of qudrtic fuctio is f ( ) c, where 0. c This c lso e writte s (if did equl zero, we would e left with The grph of qudrtic fuctio

More information

Chapter 2: Probability and Statistics

Chapter 2: Probability and Statistics Wter 4 Che 35: Sttstcl Mechcs Checl Ketcs Itroucto to sttstcs... 7 Cotuous Dstrbutos... 9 Guss Dstrbuto (D)... Coutg evets to etere probbltes... Bol Coeffcets (Dstrbuto)... 3 Strlg s Appoto... 4 Guss Approto

More information

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl Alyss for Egeers Germ Jord Uversty ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl soluto of lrge systems of ler lgerc equtos usg drect methods such s Mtr Iverse, Guss

More information

Math 153: Lecture Notes For Chapter 1

Math 153: Lecture Notes For Chapter 1 Mth : Lecture Notes For Chpter Sectio.: Rel Nubers Additio d subtrctios : Se Sigs: Add Eples: = - - = - Diff. Sigs: Subtrct d put the sig of the uber with lrger bsolute vlue Eples: - = - = - Multiplictio

More information

Numerical Analysis Topic 4: Least Squares Curve Fitting

Numerical Analysis Topic 4: Least Squares Curve Fitting Numerl Alss Top 4: Lest Squres Curve Fttg Red Chpter 7 of the tetook Alss_Numerk Motvto Gve set of epermetl dt: 3 5. 5.9 6.3 The reltoshp etwee d m ot e ler. Fd futo f tht est ft the dt 3 Alss_Numerk Motvto

More information

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table.

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table. CURVE FITTING Obectve curve ttg s t represet set dscrete dt b uct curve. Csder set dscrete dt s gve tble. 3 3 = T use the dt eectvel, curve epress s tted t the gve dt set, s = + = + + = e b ler uct plml

More information

On Several Inequalities Deduced Using a Power Series Approach

On Several Inequalities Deduced Using a Power Series Approach It J Cotemp Mth Sceces, Vol 8, 203, o 8, 855-864 HIKARI Ltd, wwwm-hrcom http://dxdoorg/02988/jcms2033896 O Severl Iequltes Deduced Usg Power Seres Approch Lored Curdru Deprtmet of Mthemtcs Poltehc Uversty

More information

Regression. By Jugal Kalita Based on Chapter 17 of Chapra and Canale, Numerical Methods for Engineers

Regression. By Jugal Kalita Based on Chapter 17 of Chapra and Canale, Numerical Methods for Engineers Regresso By Jugl Klt Bsed o Chpter 7 of Chpr d Cle, Numercl Methods for Egeers Regresso Descrbes techques to ft curves (curve fttg) to dscrete dt to obt termedte estmtes. There re two geerl pproches two

More information

Sequences and summations

Sequences and summations Lecture 0 Sequeces d summtos Istructor: Kgl Km CSE) E-ml: kkm0@kokuk.c.kr Tel. : 0-0-9 Room : New Mleum Bldg. 0 Lb : New Egeerg Bldg. 0 All sldes re bsed o CS Dscrete Mthemtcs for Computer Scece course

More information

CS321. Numerical Analysis

CS321. Numerical Analysis CS Numercl Alyss Lecture 4 Numercl Itegrto Proessor Ju Zg Deprtmet o Computer Scece Uversty o Ketucky Legto, KY 456 6 Octoer 6, 5 Dete Itegrl A dete tegrl s tervl or tegrto. For ed tegrto tervl, te result

More information

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y 4. Le Itegrls I ths secto we defe tegrl tht s smlr to sgle tegrl except tht sted of tegrtg over tervl [ ] we tegrte over curve. Such tegrls re clled le tegrls lthough curve tegrls would e etter termology.

More information

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS PubH 745: REGRESSION ANALSIS REGRESSION IN MATRIX TERMS A mtr s dspl of umbers or umercl quttes ld out rectgulr rr of rows d colums. The rr, or two-w tble of umbers, could be rectgulr or squre could be

More information

Chapter 2 Intro to Math Techniques for Quantum Mechanics

Chapter 2 Intro to Math Techniques for Quantum Mechanics Wter 3 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...

More information

MATLAB PROGRAM FOR THE NUMERICAL SOLUTION OF DUHAMEL CONVOLUTION INTEGRAL

MATLAB PROGRAM FOR THE NUMERICAL SOLUTION OF DUHAMEL CONVOLUTION INTEGRAL Bullet of te Trslv Uversty of Brşov Vol 5 (54-1 Seres 1: Specl Issue No 1 MATLAB PROGRAM FOR THE NUMERICAL SOLUTION OF DUHAMEL CONVOLUTION INTEGRAL M BOTIŞ 1 Astrct: I te ler lyss of structures troug modl

More information

Solutions Manual for Polymer Science and Technology Third Edition

Solutions Manual for Polymer Science and Technology Third Edition Solutos ul for Polymer Scece d Techology Thrd Edto Joel R. Fred Uer Sddle Rver, NJ Bosto Idols S Frcsco New York Toroto otrel Lodo uch Prs drd Cetow Sydey Tokyo Sgore exco Cty Ths text s ssocted wth Fred/Polymer

More information

Numerical Methods for Eng [ENGR 391] [Lyes KADEM 2007] Direct Method; Newton s Divided Difference; Lagrangian Interpolation; Spline Interpolation.

Numerical Methods for Eng [ENGR 391] [Lyes KADEM 2007] Direct Method; Newton s Divided Difference; Lagrangian Interpolation; Spline Interpolation. Nuecl Methods o Eg [ENGR 39 [Les KADEM 7 CHAPTER V Itepolto d Regesso Topcs Itepolto Regesso Dect Method; Newto s Dvded Deece; Lgg Itepolto; ple Itepolto Le d o-le Wht s tepolto? A ucto s ote gve ol t

More information

Differential Entropy 吳家麟教授

Differential Entropy 吳家麟教授 Deretl Etropy 吳家麟教授 Deto Let be rdom vrble wt cumultve dstrbuto ucto I F s cotuous te r.v. s sd to be cotuous. Let = F we te dervtve s deed. I te s clled te pd or. Te set were > 0 s clled te support set

More information

COMPLEX NUMBERS AND DE MOIVRE S THEOREM

COMPLEX NUMBERS AND DE MOIVRE S THEOREM COMPLEX NUMBERS AND DE MOIVRE S THEOREM OBJECTIVE PROBLEMS. s equl to b d. 9 9 b 9 9 d. The mgr prt of s 5 5 b 5. If m, the the lest tegrl vlue of m s b 8 5. The vlue of 5... s f s eve, f s odd b f s eve,

More information

Unit 1 Chapter-3 Partial Fractions, Algebraic Relationships, Surds, Indices, Logarithms

Unit 1 Chapter-3 Partial Fractions, Algebraic Relationships, Surds, Indices, Logarithms Uit Chpter- Prtil Frctios, Algeric Reltioships, Surds, Idices, Logriths. Prtil Frctios: A frctio of the for 7 where the degree of the uertor is less th the degree of the deoitor is referred to s proper

More information

24 Concept of wave function. x 2. Ae is finite everywhere in space.

24 Concept of wave function. x 2. Ae is finite everywhere in space. 4 Cocept of wve fucto Chpter Cocept of Wve Fucto. Itroucto : There s lwys qutty sscocte wth y type of wves, whch vres peroclly wth spce te. I wter wves, the qutty tht vres peroclly s the heght of the wter

More information

Numerical Differentiation and Integration

Numerical Differentiation and Integration Numerl Deretto d Itegrto Overvew Numerl Deretto Newto-Cotes Itegrto Formuls Trpezodl rule Smpso s Rules Guss Qudrture Cheyshev s ormul Numerl Deretto Forwrd te dvded deree Bkwrd te dvded deree Ceter te

More information

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector evel-2 BS trx-vector opertos wth 2 opertos sequetlly BS-Notto: S --- sgle precso G E geerl mtrx V --- vector defes SGEV, mtrx-vector product: r y r α x β r y ther evel-2 BS: Solvg trgulr system x wth trgulr

More information

Chapter 5. Curve fitting

Chapter 5. Curve fitting Chapter 5 Curve ttg Assgmet please use ecell Gve the data elow use least squares regresso to t a a straght le a power equato c a saturato-growthrate equato ad d a paraola. Fd the r value ad justy whch

More information

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

Chapter Simpson s 1/3 Rule of Integration. ( x) Cpter 7. Smpso s / Rule o Itegrto Ater redg ts pter, you sould e le to. derve te ormul or Smpso s / rule o tegrto,. use Smpso s / rule t to solve tegrls,. develop te ormul or multple-segmet Smpso s / rule

More information

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS Jourl of Algebr Nuber Theory: Advces d Applctos Volue 6 Nuber 6 ges 85- Avlble t http://scetfcdvces.co. DOI: http://dx.do.org/.864/t_779 ON NILOTENCY IN NONASSOCIATIVE ALGERAS C. J. A. ÉRÉ M. F. OUEDRAOGO

More information

Chapter 1. Infinite Sequences and Series. 1.1 Sequences. A sequence is a set of numbers written in a definite order

Chapter 1. Infinite Sequences and Series. 1.1 Sequences. A sequence is a set of numbers written in a definite order hpter Ite Sequeces d Seres. Sequeces A sequece s set o umers wrtte dete order,,,... The umer s clled the rst term, s clled the secod term, d geerl s th clled the term. Deto.. The sequece {,,...} s usull

More information

Analele Universităţii din Oradea, Fascicula: Protecţia Mediului, Vol. XIII, 2008

Analele Universităţii din Oradea, Fascicula: Protecţia Mediului, Vol. XIII, 2008 Alele Uverstăţ d Orde Fsul: Proteţ Medulu Vol. XIII 00 THEORETICAL AND COMPARATIVE STUDY REGARDING THE MECHANICS DISPLASCEMENTS UNDER THE STATIC LOADINGS FOR THE SQUARE PLATE MADE BY WOOD REFUSE AND MASSIF

More information

An Ising model on 2-D image

An Ising model on 2-D image School o Coputer Scence Approte Inerence: Loopy Bele Propgton nd vrnts Prolstc Grphcl Models 0-708 Lecture 4, ov 7, 007 Receptor A Knse C Gene G Receptor B Knse D Knse E 3 4 5 TF F 6 Gene H 7 8 Hetunndn

More information

M098 Carson Elementary and Intermediate Algebra 3e Section 10.2

M098 Carson Elementary and Intermediate Algebra 3e Section 10.2 M09 Crso Eleetry d Iteredite Alger e Sectio 0. Ojectives. Evlute rtiol epoets.. Write rdicls s epressios rised to rtiol epoets.. Siplify epressios with rtiol uer epoets usig the rules of epoets.. Use rtiol

More information

Some Estimators for the Population Mean Using Auxiliary Information Under Ranked Set Sampling

Some Estimators for the Population Mean Using Auxiliary Information Under Ranked Set Sampling Jourl of Moder Appled Sttstcl Methods Volue 8 Issue Artcle 4 5--009 Soe Esttors for the Populto Me Usg Aulr Iforto Uder ked Set Splg Wld A. Abu-Deh Sult Qboos Uverst budeh@hoo.co M. S. Ahed Sult Qboos

More information

Construction of Canonical Polynomial Basis Functions for Solving Special N th -Order Linear Integro-Differential Equations

Construction of Canonical Polynomial Basis Functions for Solving Special N th -Order Linear Integro-Differential Equations Aerc Jourl of Egeerg Reserch AJER Aerc Jourl of Egeerg Reserch AJER e-iss : -87 p-iss : -9 Volue- Issue-5 pp-- wwwerus Reserch per Ope Access Costructo of Cocl olol Bss Fuctos for Solg Specl th -Orer er

More information

Roberto s Notes on Integral Calculus Chapter 4: Definite integrals and the FTC Section 2. Riemann sums

Roberto s Notes on Integral Calculus Chapter 4: Definite integrals and the FTC Section 2. Riemann sums Roerto s Notes o Itegrl Clculus Chpter 4: Defte tegrls d the FTC Secto 2 Rem sums Wht you eed to kow lredy: The defto of re for rectgle. Rememer tht our curret prolem s how to compute the re of ple rego

More information

FORMULAE FOR FINITE DIFFERENCE APPROXIMATIONS, QUADRATURE AND LINEAR MULTISTEP METHODS

FORMULAE FOR FINITE DIFFERENCE APPROXIMATIONS, QUADRATURE AND LINEAR MULTISTEP METHODS Jourl o Mtemtcl Sceces: Advces d Alctos Volume Number - Pges -9 FRMULAE FR FINITE DIFFERENCE APPRXIMATINS QUADRATURE AND LINEAR MULTISTEP METHDS RAMESH KUMAR MUTHUMALAI Dertmet o Mtemtcs D G Vsv College

More information

INTEGRATION TECHNIQUES FOR TWO DIMENSIONAL DOMAINS

INTEGRATION TECHNIQUES FOR TWO DIMENSIONAL DOMAINS IJRET: Itertol Jourl of Reserch Egeerg d Techolog eissn: 9-6 pissn: -78 INTEGRATION TECHNIQUES FOR TWO DIMENSIONAL DOMAINS Logh Peruml Lecturer, Fcult of Egeerg d Techolog, Multmed Uverst, Mlcc, Mls Astrct

More information

Generalized Hybrid Grey Relation Method for Multiple Attribute Mixed Type Decision Making*

Generalized Hybrid Grey Relation Method for Multiple Attribute Mixed Type Decision Making* Geerlzed Hybrd Grey Relto Method for Multple Attrbute Med Type Decso Mkg Gol K Yuchol Jog Sfeg u b Ceter of Nturl Scece versty of Sceces Pyogyg DPR Kore b College of Ecoocs d Mgeet Ng versty of Aeroutcs

More information

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +.

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +. Ler Trsfortos d Group Represettos Hoework #3 (06-07, Aswers Q-Q re further exerses oer dots, self-dot trsfortos, d utry trsfortos Q3-6 volve roup represettos Of these, Q3 d Q4 should e quk Q5 s espelly

More information

On a class of analytic functions defined by Ruscheweyh derivative

On a class of analytic functions defined by Ruscheweyh derivative Lfe Scece Jourl ;9( http://wwwlfescecestecom O clss of lytc fuctos defed by Ruscheweyh dervtve S N Ml M Arf K I Noor 3 d M Rz Deprtmet of Mthemtcs GC Uversty Fslbd Pujb Pst Deprtmet of Mthemtcs Abdul Wl

More information

Module 2: Introduction to Numerical Analysis

Module 2: Introduction to Numerical Analysis CY00 Itroducto to Computtol Chemtr Autum 00-0 Module : Itroducto to umercl Al Am of the preet module. Itroducto to c umercl l. Developg mple progrm to mplemet the umercl method opc of teret. Iterpolto:

More information

Rendering Equation. Linear equation Spatial homogeneous Both ray tracing and radiosity can be considered special case of this general eq.

Rendering Equation. Linear equation Spatial homogeneous Both ray tracing and radiosity can be considered special case of this general eq. Rederg quto Ler equto Sptl homogeeous oth ry trcg d rdosty c be cosdered specl cse of ths geerl eq. Relty ctul photogrph Rdosty Mus Rdosty Rederg quls the dfferece or error mge http://www.grphcs.corell.edu/ole/box/compre.html

More information

6. Chemical Potential and the Grand Partition Function

6. Chemical Potential and the Grand Partition Function 6. Chemcl Potetl d the Grd Prtto Fucto ome Mth Fcts (see ppedx E for detls) If F() s lytc fucto of stte vrles d such tht df d pd the t follows: F F p lso sce F p F we c coclude: p I other words cross dervtves

More information

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares Itertol Jourl of Scetfc d Reserch Publctos, Volume, Issue, My 0 ISSN 0- A Techque for Costructg Odd-order Mgc Squres Usg Bsc Lt Squres Tomb I. Deprtmet of Mthemtcs, Mpur Uversty, Imphl, Mpur (INDIA) tombrom@gml.com

More information

4 Linear Homogeneous Recurrence Relation 4-1 Fibonacci Rabbits. 组合数学 Combinatorics

4 Linear Homogeneous Recurrence Relation 4-1 Fibonacci Rabbits. 组合数学 Combinatorics 4 Ler Homogeeous Recurrece Relto 4- bocc Rbbts 组合数学 ombtorcs The delt of the th moth d - th moth s gve brth by the rbbts - moth. o = - + - Moth Moth Moth Moth 4 I the frst moth there s pr of ewly-bor rbbts;

More information

The Distribution of Minimizing Maximum Entropy: Alternative to Weibull distribution for wind speed

The Distribution of Minimizing Maximum Entropy: Alternative to Weibull distribution for wind speed Proceedgs o the 9th WSEAS Itertol Coerece o Appled Mthetcs, Istul, urey, My 7-9, 6 (pp65-6) he Dstruto o Mzg Mxu Etropy: Altertve to Weull dstruto or wd speed ALADDI SHAMILOV, ILHA USA, YELIZ MER KAAR

More information

Systems of second order ordinary differential equations

Systems of second order ordinary differential equations Ffth order dgolly mplct Ruge-Kutt Nystrom geerl method solvg secod Order IVPs Fudzh Isml Astrct A dgolly mplct Ruge-Kutt-Nystróm Geerl (SDIRKNG) method of ffth order wth explct frst stge for the tegrto

More information

Image stitching. Image stitching. Video summarization. Applications of image stitching. Stitching = alignment + blending. geometrical registration

Image stitching. Image stitching. Video summarization. Applications of image stitching. Stitching = alignment + blending. geometrical registration Ige sttchg Sttchg = lget + ledg Ige sttchg geoetrcl regstrto photoetrc regstrto Dgtl Vsul Effects Yug-Yu Chug wth sldes Rchrd Szelsk, Steve Setz, Mtthew Brow d Vclv Hlvc Applctos of ge sttchg Vdeo stlzto

More information

Research on green machine product design evaluate system based on AHP

Research on green machine product design evaluate system based on AHP ppled Mechcs d Mterls Sutted: 04-07-0 ISSN: 66-748 Vol. 680 pp 47-44 ccepted: 04-07-4 do:0.408/.scetfc.et/mm.680.47 Ole: 04-0-0 04 rs ech Pulctos Stzerld Reserch o gree che product desg evlute syste sed

More information

Chapter 7. Bounds for weighted sums of Random Variables

Chapter 7. Bounds for weighted sums of Random Variables Chpter 7. Bouds for weghted sums of Rdom Vrbles 7. Itroducto Let d 2 be two depedet rdom vrbles hvg commo dstrbuto fucto. Htczeko (998 d Hu d L (2000 vestgted the Rylegh dstrbuto d obted some results bout

More information

CS473-Algorithms I. Lecture 3. Solving Recurrences. Cevdet Aykanat - Bilkent University Computer Engineering Department

CS473-Algorithms I. Lecture 3. Solving Recurrences. Cevdet Aykanat - Bilkent University Computer Engineering Department CS473-Algorthms I Lecture 3 Solvg Recurreces Cevdet Aykt - Blket Uversty Computer Egeerg Deprtmet Solvg Recurreces The lyss of merge sort Lecture requred us to solve recurrece. Recurreces re lke solvg

More information

Differential Method of Thin Layer for Retaining Wall Active Earth Pressure and Its Distribution under Seismic Condition Li-Min XU, Yong SUN

Differential Method of Thin Layer for Retaining Wall Active Earth Pressure and Its Distribution under Seismic Condition Li-Min XU, Yong SUN Itertol Coferece o Mechcs d Cvl Egeerg (ICMCE 014) Dfferetl Method of Th Lyer for Retg Wll Actve Erth Pressure d Its Dstrbuto uder Sesmc Codto L-M XU, Yog SUN Key Lbortory of Krst Evromet d Geologcl Hzrd

More information

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION St Joh s College UPPER V Mthemtcs: Pper Lerg Outcome d ugust 00 Tme: 3 hours Emer: GE Mrks: 50 Modertor: BT / SLS INSTRUCTIONS ND INFORMTION Red the followg structos crefull. Ths questo pper cossts of

More information

PAIR OF STRAIGHT LINES. will satisfy L1 L2 0, and thus L1 L. 0 represent? It is obvious that any point lying on L 1

PAIR OF STRAIGHT LINES. will satisfy L1 L2 0, and thus L1 L. 0 represent? It is obvious that any point lying on L 1 LOCUS 33 Seto - 3 PAIR OF STRAIGHT LINES Cosder two les L L Wht do ou thk wll L L represet? It s ovous tht pot lg o L d L wll stsf L L, d thus L L represets the set of pots osttutg oth the les,.e., L L

More information

Chapter 3 Supplemental Text Material

Chapter 3 Supplemental Text Material S3-. The Defto of Fctor Effects Chpter 3 Supplemetl Text Mterl As oted Sectos 3- d 3-3, there re two wys to wrte the model for sglefctor expermet, the mes model d the effects model. We wll geerlly use

More information

Strategies for the AP Calculus Exam

Strategies for the AP Calculus Exam Strteges for the AP Clculus Em Strteges for the AP Clculus Em Strtegy : Kow Your Stuff Ths my seem ovous ut t ees to e metoe. No mout of cochg wll help you o the em f you o t kow the mterl. Here s lst

More information

Some Different Perspectives on Linear Least Squares

Some Different Perspectives on Linear Least Squares Soe Dfferet Perspectves o Lear Least Squares A stadard proble statstcs s to easure a respose or depedet varable, y, at fed values of oe or ore depedet varables. Soetes there ests a deterstc odel y f (,,

More information

Linear Algebra Concepts

Linear Algebra Concepts Ler Algebr Cocepts Ke Kreutz-Delgdo (Nuo Vscocelos) ECE 75A Wter 22 UCSD Vector spces Defto: vector spce s set H where ddto d sclr multplcto re defed d stsf: ) +( + ) (+ )+ 5) l H 2) + + H 6) 3) H, + 7)

More information

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University

Advanced Algorithmic Problem Solving Le 3 Arithmetic. Fredrik Heintz Dept of Computer and Information Science Linköping University Advced Algorthmc Prolem Solvg Le Arthmetc Fredrk Hetz Dept of Computer d Iformto Scece Lköpg Uversty Overvew Arthmetc Iteger multplcto Krtsu s lgorthm Multplcto of polyomls Fst Fourer Trsform Systems of

More information

Design of Bayesian MDS Sampling Plan Based on the Process Capability Index

Design of Bayesian MDS Sampling Plan Based on the Process Capability Index World Acdey of Scece, Egeerg d Techology Vol:, No:0, 07 Desg of Byes MDS Splg Pl Bsed o the Process pblty Idex Dvood Shshebor, Mohd Sber Fllh Nezhd, S Sef Itertol Scece Idex, Idustrl d Mufcturg Egeerg

More information

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4 // Sples There re ses where polyoml terpolto s d overshoot oslltos Emple l s Iterpolto t -,-,-,-,,,,,.... - - - Ide ehd sples use lower order polyomls to oet susets o dt pots mke oetos etwee djet sples

More information

Linear Algebra Concepts

Linear Algebra Concepts Ler Algebr Cocepts Nuo Vscocelos (Ke Kreutz-Delgdo) UCSD Vector spces Defto: vector spce s set H where ddto d sclr multplcto re defed d stsf: ) +( + ) = (+ )+ 5) H 2) + = + H 6) = 3) H, + = 7) ( ) = (

More information

Outline. Finite Difference Grids. Numerical Analysis. Finite Difference Grids II. Finite Difference Grids III

Outline. Finite Difference Grids. Numerical Analysis. Finite Difference Grids II. Finite Difference Grids III Itrodcto to Nmercl Alyss Mrc, 9 Nmercl Metods or PDEs Lrry Cretto Meccl Egeerg 5B Semr Egeerg Alyss Mrc, 9 Otle Revew mdterm soltos Revew bsc mterl o mercl clcls Expressos or dervtves, error d error order

More information

Analysis of error propagation in profile measurement by using stitching

Analysis of error propagation in profile measurement by using stitching Ay o error propgto proe eureet y ug ttchg Ttuy KUME, Kzuhro ENAMI, Yuo HIGASHI, Kej UENO - Oho, Tuu, Ir, 35-8, JAPAN Atrct Sttchg techque whch ee oger eureet rge o proe ro eer eure proe hg prty oerppe

More information

If a is any non zero real or imaginary number and m is the positive integer, then a...

If a is any non zero real or imaginary number and m is the positive integer, then a... Idices d Surds.. Defiitio of Idices. If is o ero re or igir uer d is the positive iteger the...... ties. Here is ced the se d the ide power or epoet... Lws of Idices. 0 0 0. where d re rtio uers where

More information