MODELLING AND EXPERIMENTAL ANALYSIS OF MOTORCYCLE DYNAMICS USING MATLAB

Size: px
Start display at page:

Download "MODELLING AND EXPERIMENTAL ANALYSIS OF MOTORCYCLE DYNAMICS USING MATLAB"

Transcription

1 MODELLING AND EXPERIMENTAL ANALYSIS OF MOTORCYCLE DYNAMICS USING MATLAB P. Florn, P. Vrání, R. Čermá Fculy of Mechncl Engneerng, Unversy of Wes Bohem Asrc The frs pr of hs pper s devoed o mhemcl modellng of moorcycle dynmcs. A nonlner 5DOF model of moorcycle s developed usng Lgrnge equons. Ths pproch enles o smule lrge dsplcemen nlyses s well s he conc eween res nd rod. The se of nonlner dfferenl equons s solved usng consn verge cceleron mehod n MATLAB. The resuls of mulody dynmcs smulon re verfed usng VI-Moorcycle plugn for Adms/Cr nd hey re used s oundry condons for FEM nlyses. The second pr of hs pper s focused on expermenl nlyss of moorcycle dynmcs. A mesurng sysem connng hree cceleromeers ws developed nd used for rder vron exposure nlyss. D from 1.6-lomeer esng rc were processed usng MATLAB nd evlued ccordng o ČSN ISO Nonlner mhemcl model of moorcycle Frs sep of he soluon process s o develop nonlner mhemcl model of moorcycle. A plnr 5-degre-of-freedom model ws proposed wh followng generlzed coordnes: x frme horzonl rnslon; y frme rnslon; φ frme pch ngle; y fron ssemly vercl rnslon; y rer ssemly vercl rnslon. A scheme of he model connng generlzed coordnes s well s oher prmeers s shown n Fg. 1. x m,i T ϕ,,l,,l m red y y m red y Fgure 1: Scheme of he model The generlzed coordnes re ncluded n vecor q s shown n equon 1. x y y y T,,,, q (1) Lgrnge equons (eq. ) were used o develop equons of moon of he sysem. d d E q E q E p q R q Q ()

2 Where E, E p nd R represen nec energy funcon, poenl energy funcon nd Rylegh dsspon funcon of he sysem. red red m m I m m M () sn sn sn sn K () sn B (5) The sffness mrx nd he dmpng mrx re oh no consn nd depend on he generlzed coordne φ whch mens he sysem s nonlner nd le o provde more ccure resuls s dsplcemens ncrese. However, hs lso plces requremens on he negron mehod of he moon equons self. 1.1 Tre conc model Inercon eween res nd rod s sgnfcn source of forces h c on he frme. In hs cse longudnl drvng nd rng forces re negleced nd he ey s s o on norml conc forces. As sed prevously he whole model s plnr herefore lerl cornerng forces re no en no ccoun eher. The model of he re conc s shown n Fgure. rod(x) rod(x 1 ) rod(x ) r pneu c x1 S pneu () x y Fgure : Tre conc model

3 Le s ssume h he locon of re cener n nown ny me. In cse h ny pon of rod surfce s closer o he re cener hn re rdus conc pressure exerng on he re cn e clculed s p pc (6) Where p descres sffness chrcerscs of he re nd c s he dfference eween he re rdus nd he dsnce. Dfferenl norml force cn e oned ccordng o eq. 6. dn cds (7) p Dfferenl ds reles o re rc. Dfferenl norml force s lwys perpendculr o he rod surfce. For our prolem s crucl o deermne s componens n horzonl nd vercl drecon. Ths cn e ccomplshed y usng dervve of rod funcon s descred n he followng equons. dn dn x x drod pc sn rcn dx dx (8) drod pc rcn dx dx (9) In order o deermne he componens of he cul norml force, negron s conduced s he very ls sep. xs pneu rpneu N dn x (1) x x S r pneu pneu ys pneu rpneu N dn y (11) y y S r pneu pneu The re conc model proposed ove s sed on elsc conc model. Tre hyseress effecs cn e en no consderon s well ssumng dmpng forces hve smlr chrcer o norml conc forces s sed n he followng equon. N cn (1) The vrle from prevous equon reles o re deformon re. Numercl negron of he equons of moon Once we cqured he forces cng on res we cn proceed o he soluon process of he moon equons wh MATLAB. Se of 5 nonlner ordnry dfferenl equons s summed up n he Equon 1. Mq Bq Kq fn q,q, (1)

4 Consn verge cceleron negron mehod ws used due o s relve smplcy nd numercl sly. Ths mehod s predcor-correcor sed s he sysem n queson s nonlner. A rod funcon ws desgned usng modfed sn funcons o represen n oscle whch s supposed o cuse loss of conc eween he res nd he rod. In hs wy jump of moorcycle cn e smuled. hegh [mm] 1 Fgure : Rod profle Consn verge cceleron mehod s sed on n ssumpon h he cceleron s consn eween wo pons n me (Equon 1). q 1 q q (1) By negron of he prevous equon we on formuls for veloces nd dsplcemens. q q q q (15) q q q q q (16) Susung Equons 1 nd 15 no Equon 1 leds o: ~ Zq f (17) Therefore he cceleron n he nex me sep s clculed s: q 1~ (18) Z f Acceleron resuls re shown n he fgures elow. In Fgure here re cceleron resuls of he frme. The nl seep ncrese reles o he egnnng of he oscle. As he cceleron drops o pproxmely -1 ms - mens h he res los conc wh surfce. The pe vlues occur fer lndng rechng 6 ms -. Acceleron resuls of fron nd rer ssemly n Fgure 5 cn e explned n smlr wy.

5 frme 5 fron ssemly rer ssemly 15 cceleron [m*s-] 1 cceleron [m*s-] me Fgure : Frme cceleron resuls -15 me Fgure 5: Fron nd rer cceleron resuls The mhemcl model h ws developed provdes resonle resuls; however, furher verfcon s necessry. In order o do so, ADAMS/VI-Moorcycle module ws used o compre resuls. In Fgure 6 here s moorcycle model n VI-Moorcycle nerfce runnng over n oscle defned n he sme s n he MATLAB model. In Fgure 7 here re cceleron resuls of fron ssemly n ADAMS nd MATLAB. In hs smulon re dmpng properes were negleced n MATLAB whch explns he ey dfference eween oh curves. Fgure 6: VI-Moorcycle model Fgure 7: Fron ssemly cceleron resul comprson Expermenl nlyss A mesuremen sysem ws desgned n order o fulfll wo purposes lsed elow y usng nexpensve prs used n uomove pplcons. 1) Mesurng dynmcs of moorcycle n moon n order o verfy compuonl model ) Evluon of moorcycle vrons effecs on he rder y pplcon of ČSN ISO61 nd ČSN EN ISO 59 sndrds For d loggng DL1 MKdlogger ws chosen. Advnges of hs dlogger re he possly of connecng up o 1 exernl sensors nd he possly of loggng d from vehcle conrol un.

6 Fgure 8: Dlogger DL1 MK [] In order o on relonshp eween oupu volge of cceleromeers nd vlues of cceleron smple expermen ws done. Durng hs expermen ech xs ws exposed o posve nd negve grvonl cceleron s well s o zero cceleron. By ssc evluon of hese hree pons lner relon eween oupu volge nd moun of cceleron ws oned. Fgure 9: Oupu sgnl of wo xs cceleromeer.1 Progrm N. 1 Processng of he mesured dgl sgnls To smplfy he processng of mesured sgnls GUI ws creed. Mn purpose of hs progrm s o conver mesured sgnls from volge o uns of cceleron y usng prevously compued lner relon. The GUI lso hs funcons med mnly verfyng funcon of sensors nd evluon of mesured d. Fgure 1: GUI nd evluon of mesured d

7 . Progrm N. Evluon of d y he mehodc of ČSN ISO 61 sndrd Ths progrm s processng oupu d of progrm N. 1 y usng ČSN ISO 61 sndrd, med effecs on helh nd comfor. The oupus of hs progrm re frequency specrum of every xs of cceleromeers, summed up moun of vrons (for comprng wh lm moun c ), effecve vlues of weghed vrons hw j nd conrollng fcor. Verfcon of hs progrm ws mde y he followng genered npu sgnl: 5 sn1 sn x,7 sn 19 (19) y x rnd n sze () Fgure 11: Oupu of he FFT lgorhm oned y usng genered npu. Progrm N. Evluon of d y he mehodc of ČSN EN ISO 59 sndrd Ths progrm s processng oupu d of progrm N. 1 y usng ČSN EN ISO 59 sndrd. Oupus of hs progrm re effecve vlues of weghed vrons nd ol dly exposon o vrons A(8). Ths evluon process cn e used only s reference o compre dfferen moorcycles. Precse evluon s no relevn ecuse he vlues recommended y hs sndrd re no men for moorcycles. Fgure 1: Rw mesured d n sw rceechnology Anlyss 8.5

8 Concluson The mhemcl model of moorcycle h ws developed s n good greemen wh commercl sofwre VI-Moorcycle. Is oupus mgh e used for consequenl FEM smulons. Furher developmen of hs model s plnned n order o conduc hree dmensonl nlyses. As fr s expermenl nlyss s concerned, correc funcon of developed progrms ws esed on d oned y mesurng dynmcs of he rel moorcycle rdng on pulc rods. Unforunely, usge of hs sysem s nowdys lmed y nsuffcen smplng frequency of dlogger nd low ndwdh of used cceleromeers. Boh ssues re currenly eng solved. References [1] D. E. Newlnd. An Inroducon o Rndom Vrons, Specrl nd Wvele Anlyss. Longmn Scenfc & Techncl, Essex, U.K., hrd edon, 199. [] J. Dupl. Výpočové meody mechny, ZČU FAV,. [] Rce echnology dlogger DL1 MK [onlne]. [c ]. Avlle :hp:// [] V. Cossler. Moorcycle Dynmcs. Lulu Press, U.K., 6. [5] T. Fole. Moorcycle Hndlng nd Chsss Desgn, he r nd scence. Spn,. [6] P. Florn. Modelng of moorcycles nd her componens, Mser s hess, Unversy of Wes Bohem, Plsen, 15. [7] P. Vrání. Expermenl nd compuonl echnques for modelng of moorcycles nd her componens, Bchelors hess, Unversy of Wes Bohem, Plsen, 15. Ing. Pvel Florn pflorn@s.zcu.cz Bc. Pvel Vrání vrnp@sudens.zcu.cz Ing. Romn Čermá, Ph.D. rcerm@s.zcu.cz

Electromagnetic Transient Simulation of Large Power Transformer Internal Fault

Electromagnetic Transient Simulation of Large Power Transformer Internal Fault Inernonl Conference on Advnces n Energy nd Envronmenl Scence (ICAEES 5) Elecromgnec Trnsen Smulon of rge Power Trnsformer Inernl Ful Jun u,, Shwu Xo,, Qngsen Sun,c, Huxng Wng,d nd e Yng,e School of Elecrcl

More information

Advanced Electromechanical Systems (ELE 847)

Advanced Electromechanical Systems (ELE 847) (ELE 847) Dr. Smr ouro-rener Topc 1.4: DC moor speed conrol Torono, 2009 Moor Speed Conrol (open loop conrol) Consder he followng crcu dgrm n V n V bn T1 T 5 T3 V dc r L AA e r f L FF f o V f V cn T 4

More information

Numerical Simulations of Femtosecond Pulse. Propagation in Photonic Crystal Fibers. Comparative Study of the S-SSFM and RK4IP

Numerical Simulations of Femtosecond Pulse. Propagation in Photonic Crystal Fibers. Comparative Study of the S-SSFM and RK4IP Appled Mhemcl Scences Vol. 6 1 no. 117 5841 585 Numercl Smulons of Femosecond Pulse Propgon n Phoonc Crysl Fbers Comprve Sudy of he S-SSFM nd RK4IP Mourd Mhboub Scences Fculy Unversy of Tlemcen BP.119

More information

INVESTIGATION OF HABITABILITY INDICES OF YTU GULET SERIES IN VARIOUS SEA STATES

INVESTIGATION OF HABITABILITY INDICES OF YTU GULET SERIES IN VARIOUS SEA STATES Brodogrdnj/Shpuldng Volume 65 Numer 3, 214 Ferd Ckc Muhsn Aydn ISSN 7-215X eissn 1845-5859 INVESTIGATION OF HABITABILITY INDICES OF YTU GULET SERIES IN VARIOUS SEA STATES UDC 629.5(5) Professonl pper Summry

More information

To Possibilities of Solution of Differential Equation of Logistic Function

To Possibilities of Solution of Differential Equation of Logistic Function Arnold Dávd, Frnše Peller, Rená Vooroosová To Possbles of Soluon of Dfferenl Equon of Logsc Funcon Arcle Info: Receved 6 My Acceped June UDC 7 Recommended con: Dávd, A., Peller, F., Vooroosová, R. ().

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

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

Macroscopic quantum effects generated by the acoustic wave in a molecular magnet

Macroscopic quantum effects generated by the acoustic wave in a molecular magnet Cudnovsky-Fes-09034 Mcroscopc qunum effecs genered by e cousc wve n moleculr mgne Gwng-Hee Km ejong Unv., Kore Eugene M. Cudnovksy Lemn College, CUNY Acknowledgemens D. A. Grnn Lemn College, CUNY Oulne

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

Generation of Crowned Parabolic Novikov gears

Generation of Crowned Parabolic Novikov gears Engneerng Leers, 5:, EL_5 4 Generon o Crowned Prol Novkov gers Somer M. Ny, Memer, IAENG, Mohmmd Q. Adullh, nd Mohmmed N.Mohmmed Asr - The Wldher-Novkov ger s one o he rulr r gers, whh hs he lrge on re

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

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

Hidden Markov Model. a ij. Observation : O1,O2,... States in time : q1, q2,... All states : s1, s2,..., sn

Hidden Markov Model. a ij. Observation : O1,O2,... States in time : q1, q2,... All states : s1, s2,..., sn Hdden Mrkov Model S S servon : 2... Ses n me : 2... All ses : s s2... s 2 3 2 3 2 Hdden Mrkov Model Con d Dscree Mrkov Model 2 z k s s s s s s Degree Mrkov Model Hdden Mrkov Model Con d : rnson roly from

More information

Multi-load Optimal Design of Burner-inner-liner Under Performance Index Constraint by Second-Order Polynomial Taylor Series Method

Multi-load Optimal Design of Burner-inner-liner Under Performance Index Constraint by Second-Order Polynomial Taylor Series Method , 0005 (06) DOI: 0.05/ mecconf/06700005 ICMI 06 Mul-lod Opml Desgn of Burner-nner-lner Under Performnce Index Consrn by Second-Order Polynoml ylor Seres Mehod U Goqo, Wong Chun Nm, Zheng Mn nd ng Kongzheng

More information

Motion Feature Extraction Scheme for Content-based Video Retrieval

Motion Feature Extraction Scheme for Content-based Video Retrieval oon Feure Exrcon Scheme for Conen-bsed Vdeo Rerevl Chun Wu *, Yuwen He, L Zho, Yuzhuo Zhong Deprmen of Compuer Scence nd Technology, Tsnghu Unversy, Bejng 100084, Chn ABSTRACT Ths pper proposes he exrcon

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

AN INTRODUCTORY GUIDELINE FOR THE USE OF BAYESIAN STATISTICAL METHODS IN THE ANALYSIS OF ROAD TRAFFIC ACCIDENT DATA

AN INTRODUCTORY GUIDELINE FOR THE USE OF BAYESIAN STATISTICAL METHODS IN THE ANALYSIS OF ROAD TRAFFIC ACCIDENT DATA AN INTRODUCTORY GUIDELINE FOR THE USE OF BAYESIAN STATISTICAL METHODS IN THE ANALYSIS OF ROAD TRAFFIC ACCIDENT DATA CJ Molle Pr Eng Chef Engneer : Trffc Engneerng Deprmen of Economc Affrs, Agrculure nd

More information

Modeling of Jitter Characteristics for the Second Order Bang-Bang CDR

Modeling of Jitter Characteristics for the Second Order Bang-Bang CDR Modelng of Jer hrcerscs for he Second Order Bng-Bng D H Adrng nd Hossen Mr Nm eceved Aug ; receved n revsed 8 Se ; cceed 3 Oc ABSA Bng-Bng clock nd d recovery BBD crcus re hrd nonlner sysems due o he nonlnery

More information

Origin Destination Transportation Models: Methods

Origin Destination Transportation Models: Methods In Jr. of Mhemcl Scences & Applcons Vol. 2, No. 2, My 2012 Copyrgh Mnd Reder Publcons ISSN No: 2230-9888 www.journlshub.com Orgn Desnon rnsporon Models: Mehods Jyo Gup nd 1 N H. Shh Deprmen of Mhemcs,

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

ANOTHER CATEGORY OF THE STOCHASTIC DEPENDENCE FOR ECONOMETRIC MODELING OF TIME SERIES DATA

ANOTHER CATEGORY OF THE STOCHASTIC DEPENDENCE FOR ECONOMETRIC MODELING OF TIME SERIES DATA Tn Corn DOSESCU Ph D Dre Cner Chrsn Unversy Buchres Consnn RAISCHI PhD Depren of Mhecs The Buchres Acdey of Econoc Sudes ANOTHER CATEGORY OF THE STOCHASTIC DEPENDENCE FOR ECONOMETRIC MODELING OF TIME SERIES

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

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

кафедра математической экономики, Бакинский государственный университет, г. Баку, Азербайджанская Республика

кафедра математической экономики, Бакинский государственный университет, г. Баку, Азербайджанская Республика An exsence heorem or uzzy prl derenl equon Eendyev H Rusmov L Repulc o Azerjn) Теорема о существовании нечеткого дифференциального уравнения в частных производных Эфендиева Х Д Рустамова Л А Азербайджанская

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

S Radio transmission and network access Exercise 1-2

S Radio transmission and network access Exercise 1-2 S-7.330 Rdio rnsmission nd nework ccess Exercise 1 - P1 In four-symbol digil sysem wih eqully probble symbols he pulses in he figure re used in rnsmission over AWGN-chnnel. s () s () s () s () 1 3 4 )

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

Simplified Variance Estimation for Three-Stage Random Sampling

Simplified Variance Estimation for Three-Stage Random Sampling Deprmen of ppled Sscs Johnnes Kepler Unversy Lnz IFS Reserch Pper Seres 04-67 Smplfed rnce Esmon for Three-Sge Rndom Smplng ndres Quember Ocober 04 Smplfed rnce Esmon for Three-Sge Rndom Smplng ndres Quember

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

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

Acoustic and flexural wave energy conservation for a thin plate in a fluid

Acoustic and flexural wave energy conservation for a thin plate in a fluid cousc nd fleurl wve energy conservon for hn ple n flud rryl MCMHON 1 Mrme vson efence Scence nd Technology Orgnson HMS Srlng W usrl STRCT lhough he equons of fleurl wve moon for hn ple n vcuum nd flud

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

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

TSS = SST + SSE An orthogonal partition of the total SS

TSS = SST + SSE An orthogonal partition of the total SS ANOVA: Topc 4. Orhogonal conrass [ST&D p. 183] H 0 : µ 1 = µ =... = µ H 1 : The mean of a leas one reamen group s dfferen To es hs hypohess, a basc ANOVA allocaes he varaon among reamen means (SST) equally

More information

Reinforcement Learning for a New Piano Mover s Problem

Reinforcement Learning for a New Piano Mover s Problem Renforcemen Lernng for New Pno Mover s Problem Yuko ISHIWAKA Hkode Nonl College of Technology, Hkode, Hokkdo, Jpn Tomohro YOSHIDA Murorn Insue of Technology, Murorn, Hokkdo, Jpn nd Yuknor KAKAZU Reserch

More information

Power Series Solutions for Nonlinear Systems. of Partial Differential Equations

Power Series Solutions for Nonlinear Systems. of Partial Differential Equations Appled Mhemcl Scences, Vol. 6, 1, no. 14, 5147-5159 Power Seres Soluons for Nonlner Sysems of Prl Dfferenl Equons Amen S. Nuser Jordn Unversy of Scence nd Technology P. O. Bo 33, Irbd, 11, Jordn nuser@us.edu.o

More information

OPERATOR-VALUED KERNEL RECURSIVE LEAST SQUARES ALGORITHM

OPERATOR-VALUED KERNEL RECURSIVE LEAST SQUARES ALGORITHM 3rd Europen Sgnl Processng Conference EUSIPCO OPERATOR-VALUED KERNEL RECURSIVE LEAST SQUARES ALGORITM P. O. Amblrd GIPSAlb/CNRS UMR 583 Unversé de Grenoble Grenoble, Frnce. Kdr LIF/CNRS UMR 779 Ax-Mrselle

More information

Cubic Bezier Homotopy Function for Solving Exponential Equations

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

More information

Go over vector and vector algebra Displacement and position in 2-D Average and instantaneous velocity in 2-D Average and instantaneous acceleration

Go over vector and vector algebra Displacement and position in 2-D Average and instantaneous velocity in 2-D Average and instantaneous acceleration Mh Csquee Go oe eco nd eco lgeb Dsplcemen nd poson n -D Aege nd nsnneous eloc n -D Aege nd nsnneous cceleon n -D Poecle moon Unfom ccle moon Rele eloc* The componens e he legs of he gh ngle whose hpoenuse

More information

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

Parameter estimation method using an extended Kalman Filter

Parameter estimation method using an extended Kalman Filter Unvers o Wollongong Reserch Onlne cul o Engneerng nd Inormon cences - Ppers: Pr A cul o Engneerng nd Inormon cences 007 Prmeer esmon mehod usng n eended lmn ler Emmnuel D. Blnchrd Unvers o Wollongong eblnch@uow.edu.u

More information

Variants of Pegasos. December 11, 2009

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

More information

FTCS Solution to the Heat Equation

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

More information

Reconstruction of transient vibration and sound radiation of an impacted plate

Reconstruction of transient vibration and sound radiation of an impacted plate INTE-NOIE 06 econsrucon of rnsen vbron nd sound rdon of n mpced ple Ln en ; Chun-Xn B ; Xo-Zhen Zhn ; Yon-Bn Zhn 4 ; Ln Xu 5,,,4,5 Insue of ound nd Vbron eserch, efe Unversy of Technoloy, 9 Tunx od, efe

More information

Definition of Tracking

Definition of Tracking Trckng Defnton of Trckng Trckng: Generte some conclusons bout the moton of the scene, objects, or the cmer, gven sequence of mges. Knowng ths moton, predct where thngs re gong to project n the net mge,

More information

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

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

More information

A Kalman filtering simulation

A Kalman filtering simulation A Klmn filering simulion The performnce of Klmn filering hs been esed on he bsis of wo differen dynmicl models, ssuming eiher moion wih consn elociy or wih consn ccelerion. The former is epeced o beer

More information

On One Analytic Method of. Constructing Program Controls

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

More information

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

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

MTH 146 Class 11 Notes

MTH 146 Class 11 Notes 8.- Are of Surfce of Revoluion MTH 6 Clss Noes Suppose we wish o revolve curve C round n is nd find he surfce re of he resuling solid. Suppose f( ) is nonnegive funcion wih coninuous firs derivive on he

More information

FM Applications of Integration 1.Centroid of Area

FM Applications of Integration 1.Centroid of Area FM Applicions of Inegrion.Cenroid of Are The cenroid of ody is is geomeric cenre. For n ojec mde of uniform meril, he cenroid coincides wih he poin which he ody cn e suppored in perfecly lnced se ie, is

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

Experimental Design and the Analysis of Variance

Experimental Design and the Analysis of Variance Expermenl Desgn nd he nlyss of Vrnce Comprng > Groups - Numerc Responses Exenson of Mehods used o Compre Groups Independen Smples nd Pred D Desgns Norml nd non-norml d dsruons D Desgn Independen Smples

More information

An improved statistical disclosure attack

An improved statistical disclosure attack In J Grnulr Compung, Rough Ses nd Inellgen Sysems, Vol X, No Y, xxxx An mproved sscl dsclosure c Bn Tng* Deprmen of Compuer Scence, Clforn Se Unversy Domnguez Hlls, Crson, CA, USA Eml: bng@csudhedu *Correspondng

More information

SOME USEFUL MATHEMATICS

SOME USEFUL MATHEMATICS SOME USEFU MAHEMAICS SOME USEFU MAHEMAICS I is esy o mesure n preic he behvior of n elecricl circui h conins only c volges n currens. However, mos useful elecricl signls h crry informion vry wih ime. Since

More information

International Journal of Pure and Applied Sciences and Technology

International Journal of Pure and Applied Sciences and Technology Int. J. Pure Appl. Sc. Technol., () (), pp. 44-49 Interntonl Journl of Pure nd Appled Scences nd Technolog ISSN 9-67 Avlle onlne t www.jopst.n Reserch Pper Numercl Soluton for Non-Lner Fredholm Integrl

More information

Software Reliability Growth Models Incorporating Fault Dependency with Various Debugging Time Lags

Software Reliability Growth Models Incorporating Fault Dependency with Various Debugging Time Lags Sofwre Relbly Growh Models Incorporng Ful Dependency wh Vrous Debuggng Tme Lgs Chn-Yu Hung 1 Chu-T Ln 1 Sy-Yen Kuo Mchel R. Lyu 3 nd Chun-Chng Sue 4 1 Deprmen of Compuer Scence Nonl Tsng Hu Unversy Hsnchu

More information

Direct Current Circuits

Direct Current Circuits Eler urren (hrges n Moon) Eler urren () The ne moun of hrge h psses hrough onduor per un me ny pon. urren s defned s: Dre urren rus = dq d Eler urren s mesured n oulom s per seond or mperes. ( = /s) n

More information

Partially Observable Systems. 1 Partially Observable Markov Decision Process (POMDP) Formalism

Partially Observable Systems. 1 Partially Observable Markov Decision Process (POMDP) Formalism CS294-40 Lernng for Rootcs nd Control Lecture 10-9/30/2008 Lecturer: Peter Aeel Prtlly Oservle Systems Scre: Dvd Nchum Lecture outlne POMDP formlsm Pont-sed vlue terton Glol methods: polytree, enumerton,

More information

ELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION

ELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION THE 19 TH INTERNATIONAL ONFERENE ON OMPOSITE MATERIALS ELASTI MODULUS ESTIMATION OF HOPPED ARBON FIBER TAPE REINFORED THERMOPLASTIS USING THE MONTE ARLO SIMULATION Y. Sao 1*, J. Takahash 1, T. Masuo 1,

More information

Magnetostatics Bar Magnet. Magnetostatics Oersted s Experiment

Magnetostatics Bar Magnet. Magnetostatics Oersted s Experiment Mgneosics Br Mgne As fr bck s 4500 yers go, he Chinese discovered h cerin ypes of iron ore could rc ech oher nd cerin mels. Iron filings "mp" of br mgne s field Crefully suspended slivers of his mel were

More information

Version 001 test-1 swinney (57010) 1. is constant at m/s.

Version 001 test-1 swinney (57010) 1. is constant at m/s. Version 001 es-1 swinne (57010) 1 This prin-ou should hve 20 quesions. Muliple-choice quesions m coninue on he nex column or pge find ll choices before nswering. CubeUniVec1x76 001 10.0 poins Acubeis1.4fee

More information

Comparison between LETKF and EnVAR with observation localization

Comparison between LETKF and EnVAR with observation localization Comprson beeen LETKF nd EnVAR h observon loclzon * Sho Yoo Msru Kun Kzums Aonsh Se Orguch Le Duc Tuy Kb 3 Tdsh Tsuyu Meeorologcl Reserch Insue JAMSTEC 3 Meeorologcl College 6..7 D Assmlon Semnr n RIKEN/AICS

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

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore.

This document is downloaded from DR-NTU, Nanyang Technological University Library, Singapore. Ths documen s downloaded from DR-NTU, Nanyang Technologcal Unversy Lbrary, Sngapore. Tle A smplfed verb machng algorhm for word paron n vsual speech processng( Acceped verson ) Auhor(s) Foo, Say We; Yong,

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

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

Dynamic Power Allocation and Routing for Time Varying Wireless Networks

Dynamic Power Allocation and Routing for Time Varying Wireless Networks Dynmc Power Allocon nd Roung for Tme Vryng Wreless Neworks Mchel J. Neely hp://we.m.edu/mjneely/www MIT LIDS: mjneely@m.edu Asrc We consder dynmc roung nd power llocon for wreless nework wh me vryng chnnels.

More information

Chapter Lagrangian Interpolation

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

More information

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

Principle Component Analysis

Principle Component Analysis Prncple Component Anlyss Jng Go SUNY Bufflo Why Dmensonlty Reducton? We hve too mny dmensons o reson bout or obtn nsghts from o vsulze oo much nose n the dt Need to reduce them to smller set of fctors

More information

Person Movement Prediction Using Hidden Markov Models

Person Movement Prediction Using Hidden Markov Models Person Movemen Predcon Usng dden Mrkov Models Arpd Geller Lucn Vnn Compuer Scence Deprmen Lucn Blg Unversy of Su E Corn Sr o 4 Su-5525 omn {rpdgeller lucnvnn}@ulsuro Asrc: Uquous sysems use conex nformon

More information

Chapter 2: Evaluative Feedback

Chapter 2: Evaluative Feedback Chper 2: Evluive Feedbck Evluing cions vs. insrucing by giving correc cions Pure evluive feedbck depends olly on he cion ken. Pure insrucive feedbck depends no ll on he cion ken. Supervised lerning is

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

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

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

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

More information

BLOWUPS IN GAUGE AND CONSTRAINT MODES. Bernd Reimann, AEI in collaboration with M. Alcubierre, ICN (Mexico)

BLOWUPS IN GAUGE AND CONSTRAINT MODES. Bernd Reimann, AEI in collaboration with M. Alcubierre, ICN (Mexico) BLOWUPS IN GAUGE AND CONSTRAINT MODES Bernd Remnn, AEI n ollboron M. Aluberre, ICN (Mexo) Jen, Jnury 30, 006 1 Tops Pologes ( soks nd bloups ) n sysems of PDEs Te soure rer for vodng bloups Evoluon Sysem:

More information

Linear Response Theory: The connection between QFT and experiments

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

More information

Introduction. Section 9: HIGHER ORDER TWO DIMENSIONAL SHAPE FUNCTIONS

Introduction. Section 9: HIGHER ORDER TWO DIMENSIONAL SHAPE FUNCTIONS Secon 9: HIGHER ORDER TWO DIMESIO SHPE FUCTIOS Inroducon We ne conder hpe funcon for hgher order eleen. To do h n n orderl fhon we nroduce he concep of re coordne. Conder ere of rngulr eleen depced n he

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

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function ENGR 1990 Engineering Mhemics The Inegrl of Funcion s Funcion Previously, we lerned how o esime he inegrl of funcion f( ) over some inervl y dding he res of finie se of rpezoids h represen he re under

More information

Robustness Experiments with Two Variance Components

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

More information

A Cell Decomposition Approach to Online Evasive Path Planning and the Video Game Ms. Pac-Man

A Cell Decomposition Approach to Online Evasive Path Planning and the Video Game Ms. Pac-Man Cell Decomoson roach o Onlne Evasve Pah Plannng and he Vdeo ame Ms. Pac-Man reg Foderaro Vram Raju Slva Ferrar Laboraory for Inellgen Sysems and Conrols LISC Dearmen of Mechancal Engneerng and Maerals

More information

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

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

More information

(b) 10 yr. (b) 13 m. 1.6 m s, m s m s (c) 13.1 s. 32. (a) 20.0 s (b) No, the minimum distance to stop = 1.00 km. 1.

(b) 10 yr. (b) 13 m. 1.6 m s, m s m s (c) 13.1 s. 32. (a) 20.0 s (b) No, the minimum distance to stop = 1.00 km. 1. Answers o Een Numbered Problems Chper. () 7 m s, 6 m s (b) 8 5 yr 4.. m ih 6. () 5. m s (b).5 m s (c).5 m s (d) 3.33 m s (e) 8. ().3 min (b) 64 mi..3 h. ().3 s (b) 3 m 4..8 mi wes of he flgpole 6. (b)

More information

1.0 Electrical Systems

1.0 Electrical Systems . Elecricl Sysems The ypes of dynmicl sysems we will e sudying cn e modeled in erms of lgeric equions, differenil equions, or inegrl equions. We will egin y looking fmilir mhemicl models of idel resisors,

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 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

WiH Wei He

WiH Wei He Sysem Idenfcaon of onlnear Sae-Space Space Baery odels WH We He wehe@calce.umd.edu Advsor: Dr. Chaochao Chen Deparmen of echancal Engneerng Unversy of aryland, College Par 1 Unversy of aryland Bacground

More information

Robust Fuzzy MIMO Bang-Bang Controller for two Links Robot Manipulators

Robust Fuzzy MIMO Bang-Bang Controller for two Links Robot Manipulators usrln Journl of Bsc nd ppled Scences, 5: 07-083, 0 ISSN 99-878 Rous Fuzz MIMO Bng-Bng Conroller for wo Lnks Roo Mnpulors Mrwn., Frrukh Ng, KSM Shr, Hnm S. Unvers Teng Nsonl, Jln Ikrm-Unen, Kng, 43000,

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

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

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

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

More information

ISSN 075-7 : (7) 0 007 C ( ), E-l: ssolos@glco FPGA LUT FPGA EM : FPGA, LUT, EM,,, () FPGA (feldprogrble ge rrs) [, ] () [], () [] () [5] [6] FPGA LUT (Look-Up-Tbles) EM (Ebedded Meor locks) [7, 8] LUT

More information

A new model for limit order book dynamics

A new model for limit order book dynamics Anewmodelforlimiorderbookdynmics JeffreyR.Russell UniversiyofChicgo,GrdueSchoolofBusiness TejinKim UniversiyofChicgo,DeprmenofSisics Absrc:Thispperproposesnewmodelforlimiorderbookdynmics.Thelimiorderbookconsiss

More information

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x)

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x) Properies of Logrihms Solving Eponenil nd Logrihmic Equions Properies of Logrihms Produc Rule ( ) log mn = log m + log n ( ) log = log + log Properies of Logrihms Quoien Rule log m = logm logn n log7 =

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

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6.

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6. [~ o o :- o o ill] i 1. Mrices, Vecors, nd Guss-Jordn Eliminion 1 x y = = - z= The soluion is ofen represened s vecor: n his exmple, he process of eliminion works very smoohly. We cn elimine ll enries

More information

LOWER-BOUND APPROACH TO THE LIMIT ANALYSIS OF 3D VAULTED BLOCK MASONRY STRUCTURES. C. Casapulla 1 and D. D Ayala 2

LOWER-BOUND APPROACH TO THE LIMIT ANALYSIS OF 3D VAULTED BLOCK MASONRY STRUCTURES. C. Casapulla 1 and D. D Ayala 2 LOWER-BOUD AROAC TO TE LIMIT AALYSIS OF 3D VAULTED BLOCK MASORY STRUCTURES C. Cspull 1 nd D. D Ayl 2 1. ABSTRACT A revew of exsng lower ound pproches for dry lock msonry srucures revels lck of relle nlycl

More information