loft man s spline is a flexible strip of material, which can be clamped or weighted so it

Size: px
Start display at page:

Download "loft man s spline is a flexible strip of material, which can be clamped or weighted so it"

Transcription

1 . Parametrc B-ple. Sple Cre Sple cre were frt e a a raftg tool for arcraft a hp blg tre. A loft ma ple a flexble trp of materal, whch ca be clampe or weghte o t wll pa throgh ay mber of pot wth mooth eformato. Lobachey etgate b-ple a early a the eteeth cetry; they were cotrcte a coolto of certa probablty trbto. I 96, Schoebrg e B-ple for tattcal ata moothg, a h paper tarte the moer theory of ple approxmato. Goro a Reefel formally troce B-ple to compter ae eg [Far97].. The B-ple ba The erlyg core of the B-ple t ba or ba fcto. The orgal efto of the B-ple ba fcto e the ea of e fferece a mathematcally Parametrc B-ple

2 ole. Carl e boor etablhe the early 97 a recre relatohp for the B- ple ba. By applyg the Lebz theorem, e boor wa able to ere the followg formla for B-ple ba fcto:.,, otherwe = th B-ple ba fcto of orer. = o-ecreag et of real mber alo calle a the ot eqece. = parameter arable. Th formla how that the B-ple ba fcto of a arbtrary egree ca be tably ealate a lear combato of ba fcto of a egree lower. The obo efg featre of the ba fcto the ot eqece. The ot eqece a et of o-ecreag real mber. The arable repreet the acte area of the real mber le that efe the B-ple ba. It tae + ot or teral to efe a ba fcto. Sce the ba fcto are bae o ot fferece, the hape of the ba fcto oly epeet o the ot pacg a ot pecfc ot ale. Parametrc B-ple

3 Aother tghg featre of the B-ple t ablty to hale cae where the ot ector cota cocet ot. Hag cocet ot, or forcg ot to be cocet, a mportat tep the cre ero proce orer to ere that the cre meet certa cotty crtera. The cre ero procere wll be ce more etal later. Fgre. how the relatohp betwee a cbc ba fcto a t ot eqece. Some of the properte of the B-ple ba fcto are: Fgre.: Cbc B-ple Ba Fcto [Far97]. Parametrc B-ple

4 The m of the B-ple ba fcto for ay parameter ale wth a pecfe teral alway eqal to ;.e.,. Each ba fcto greater or eqal to zero for all parameter ale. Each ba fcto ha oly oe maxmm ale.. The B-ple cre B-ple are pecewe polyomal of egree wth C - cotty at the commo pot betwee aacet egmet. B-ple relt by mappg the elemet of a ot eqece parametrc pace to Cartea pace. A ple ealate at a ot relt a cto pot whch the commo pot hare by two aacet egmet. B-ple are completely pecfe by the cre cotrol pot, the cre orer a the B-ple ba fcto a ee the Eqato.: -. = Pot alog the cre a a fcto of parameter = cotrol pot alo ow a the weght or the pot coeffcet. = th B-ple ba fcto of orer. Parametrc B-ple

5 Fgre.: A C Cbc B-ple cre wth t cotrol polygo [Far97]. Each pot o a B-ple a weghte combato of the local cotrol pot, whch form a cotrol polygo eclog the cre. The mber of B-ple ba fcto oboly eqal to the mber of cotrol pot a th mber the meo of the fcto pace. The mber of ot eee to efe th fcto pace eqal to the meo pl t orer. Parametrc B-ple 5

6 Parametrc B-ple 6 A metoe earler, a aatage of parametrc repreetato that t ge the cre coorate-ytem epeece. The B-ple ca th be repreete a a ector of Cartea ale whch are a fcto of the parametrc ba pace a how Eqato.. z z y y x x. B-ple ca be repreete wth repect to ther ot eqece a form or oform. A cre form f the ot pacg betwee all the ot the ame. If the cre form, the acte porto of all the ba fcto form the ame hape oer each teral. If each teral traforme to a teral betwee a, a peroc ba ca be e to ealate each cre egmet. Eqato.5 how a matrx relatohp that e to ealate each teral of a peroc cbc cre. = U M D.5 U = [ ] 6 6 / M D

7 Parametrc B-ple 7 U = moomal ba M = cotat eral traformato matrx D = cotrol pot ole the th teral. If the cre o-form, the ot pacg are oer the ot eqece. The preoly ce recre algorthm Eqato. th eceary to ealate the ba fcto. Eqato.6 how the matrx relatohp for each teral of a cbc o-form B-ple cre the flly expae form. = D.6 = parameter ale; = ot teral T S S R Q R Q P P ; P ; Q ; R ; S D

8 I orer to eterme the pacg betwee the aacet ot a ot ector, fferet parametrzato techqe are e. Parametrzato metho are crcal for the moellg of B-ple ce the pacg of the ot eqece flece the ba fcto a ce before. It amot to efg the legth of each parametrc teral, whch whe mappe to moelg pace, wll efe each cre egmet. There are three fferet metho commoly e to parametrze moel cre ata; form, chor legth a cetrpetal. Thee metho are ce below. Uform Th the mplet type of parametrzato where the ot pacg choe to be etcal for each teral. Typcally, ot ale are choe to be ccee teger a how Eqato.7..7 For may cae, howeer, th metho too mpltc a gore the geometry of the moel ata pot. Chor Legth Th parametrzato bae o the tace betwee the ata pot. The ot pacg proportoal to the tace betwee the ata pot. Eqato.8 reflect th relatohp. Th parametrzato more accrately reflect the geometry of the ata pot. Parametrc B-ple 8

9 Parametrc B-ple 9.8 = th oma ot = th ata pot = ot teral Cetrpetal Th parametrzato ere from a phycal aalogy. It ee to mooth ot arato the cetrpetal force actg o a pot moto alog the cre. Th reqre the ot eqece to be proportoal to the qare root of the tace betwee the ata pot a how Eqato.9. /.9 Other parametrzato metho hae bee etgate [Far97]. All thee metho hae certa crcmtatal aatage oer the other. There a trae-off betwee geometrcal repreetato a comptato tme. Typcally, chor legth parametrzato relt a ery goo comprome. I ay eet, each parametrzato relt a fferet hape of the cre. Parametrc cbc B-ple cre are e th reearch. Lower egree polyomal o ot proe ffcet cotrol of a cre hape, a hgher egree polyomal are comptatoally more cmberome a proe to mercal error.

10 Parametrc B-ple. B-ple Srface B-ple rface are a exteo of B-ple cre. The mot commo of a B- ple rface the teor proct rface. The rface ba fcto are proct of two arate cre bae. The rface a weghte m of rface two meoal ba fcto. The weght are a rectaglar array of cotrol pot. The followg Eqato. how a mathematcal ecrpto of the teor proct B-ple rface. m l,. where, otherwe,, l l l l l otherwe,,

11 , = B-ple rface a a fcto of two arable = cotrol pot = th ba fcto of orer a a fcto of l, = th ba fcto of orer l a a fcto of = Elemet of the ot eqece atfyg the relato, For mot compter ae eg prpoe, a the cae of the cre,, a ector fcto of two parametrc ale a. A mathematcal ecrpto of th relatohp how below Eqato.. m l x, x m l, y, y. m l z, z where x, y a z are coorate moel pace. The rectaglar array of cotrol pot form what calle a cotrol et. Smlar to the B-ple cre, the B-ple rface approxmate the hape of the cotrol et. Fgre. how a bcbc B-ple rface a the correpog cotrol et. Parametrc B-ple

12 Fgre.: A b-cbc B-ple rface a t cotrol et Smlar to the B-ple cre, the B-ple rface alo a etwor of polyomal pece. Each pece of the B-ple rface a two meoally repreete part of a rface or patch. A wth a B-ple cre, each patch of a B-ple rface may be repreete by a peroc relatohp proe the ot pacg form each recto. Th a Parametrc B-ple

13 Parametrc B-ple form B-ple rface. The bcbc cae ecrbe matrx form by Eqato.., = U M D M T V T. where, U = [ ] V = [ ] 6 6 / M,,,,,,,,,,,,,,,, D If the ot eqece are ot formly pace, the the rface o-form. The ba fcto wol the hae to be ealate by the recre relatohp. The oform patch Eqato ca be repreete matrx form. Eqato. how th relatohp for the bcbc cae the compacte form., o,,,,,,,,,,,,,,,,. A how the preo two eqato, the bcbc B-ple rface affecte locally by xtee cotrol pot. Geerally, a pot o ay B-ple rface eterme oly by a local bet of cotrol pot. Alo to be ote the fact that al

14 oparametrc cre o a B-ple rface are B-ple cre themele. For tace, for a rface efe by Eqato., le of cotat,.e., = f, are B-ple cre efe by the Eqato.: f,. f Here f are the cre cotrol pot. Sce th a parameter cre whch le o the rface, t ca be ee from Eqato. that A therefore m,.5 f m f.6 f f Th property e the the to efe oparametrc cre lyg aacet to a ormal to the trm boary for rface terrogato. Smlar to cre, the two ot ector reqre to ecrbe a rface hae to be eterme g oe of the parametrzato techqe ecrbe earler. Howeer, e to the fact that a B-ple rface a teor proct a cotrcte of a array of cotrol pot, there are a mber of pot tace for each al teral, of each ot eqece. The olto typcally to calclate a gle teral tace bae o the aerage of all of the pot tace. Parametrc B-ple

15 Parametrc B-ple 5.5 Dfferetal Geometry The motato for th topc ty to ecrbe the local cre a rface properte le cratre. The ma tool e for the eelopmet of the relt the local coorate ytem, term of whch geometrc properte are ealy ecrbe a te. A ce earler for the cae of a B-ple, a cre E ca be ecrbe parametrcally a z y x, [a,b] R.7 where t Cartea coorate x, y, z, are fferetable fcto of ee Fgre.. It ame that z y x, [a,b] R.8 where the ot eote erate wth repect to. Fgre.: Parametrc cre pace[far97].

16 A trocto of a pecal local co-orate ytem calle the Freet frame, le to a pot o the cre wll gfcatly facltate the ecrpto of the local cre properte at the pot. The frame or trhero ecrbe by three mtally perpeclar ector, t, a b whoe oretato are a trace ot the cre. The ector t calle a the taget ector, calle ma ormal ector, a b calle bormal ector. Fgre.5 epct the Freet frame. Fgre.5: The Freet Frame [Far97]. The mathematcal relatohp of the three ector wth repect to the pot ge by Eqato.9 t, b t, b,.9 where eote the cro proct. Parametrc B-ple 6

17 The plae pae by the pot a the two ector t, calle the oclatg plae O. It eqato ge by r et = r -,, et =, where r eote ay pot o O. It parametrc form O, =. Fgre.6 expla the relato betwee the oclatg plae a the three mtally perpeclar ector a two other plae calle the ormal plae a the rectfyg plae. The ormal a the rectfyg plae are perpeclar to each other a each of them perpeclar to the oclatg plae tr. The ormal a the bormal ector eterme the ormal plae. It that plae whch pae throgh a pot o the cre a perpeclar to the taget le to the cre at that pot. The taget a the bormal ector eterme the rectfyg plae. Lettg the Freet frame ary wth proe a goo ea of the cre behaor pace. The rate at whch the Freet frame moe wth repect to the parameter ge a meare of the Cratre a the Toro of the cre. Cratre the rate of trg of the taget ector a ge by the relato = =. Parametrc B-ple 7

18 Fgre.6: Relato betwee the ormal plae, oclatg plae a rectfyg plae [Far97]. Toro J a meare of the amot of rotato of the oclatg plae. I other wor toro a qatty, whch cate whether the cre twtg raply or lowly. It expree mathematcally a et[,, ] J = J =. Parametrc B-ple 8

19 The cratre, toro a the three Freet frame ector t,, b are relate by the followg et of formla calle the Freet-Serret formla Eqato.. Fgre.7 lltrate thee formla t = +, = - t +J b,. b = -J A pot o a cre where = calle a pot of flecto. Sce th pot ffclt to locate mot practcal cae, aother meare calle the cratre mma employe fg a pot at whch the cratre cloe to zero a th pot ca be coere to be the flecto pot, for all practcal prpoe. Fgre.7: The geometrc meag of the Freet-Serret formla [Far97] Parametrc B-ple 9

20 A cre a to hae cratre mma at a pot where the followg coto hol tre: - - < + -. Smlarly, a cre a to hae cratre maxma at a pot where the followg hol tre: - - > Cotrat-bae B-ple Iero B-ple theory wa orgally eelope to efe a cre or a rface that approxmate a et of ata pot. Howeer, a eger ofte more terete g B-ple for terpolatg a et of ata pot rather tha approxmatg them. The ero metho aree th e by fg the cotrol pot for a B-ple cre or a rface ge a et of ata pot to be terpolate. Th proce typcally cot of ettg p a olg a ytem of lear eqato that are bae o terpolato coto that are reqre by the moel ata. Yamagch ge a olto for the ero of form cbc ple [Yama88] whle Gloama [Glo89] exte th to a o-form cae. Flemg eelope a approach to corporate e cotrat to the et of ata pot to ge the cre or rface a ere leel of cotty [Flem9a] [Flem9b]. Parametrc B-ple

21 Parametrc B-ple For a cbc cre, the ero proce typcally cot of ettg p a olg for + cotrol pot o terpolatg ata pot. eqato ca be geerate bae o thee ata pot cotrat. Th accomplhe throgh a owlege of the behaor of B-ple ba fcto. A preoly ecrbe, the ba fcto are oly locally o zero a ay cbc B-ple teral effecte by, at mot, for ba fcto. At each ot ale, howeer, oly three ba fcto are o-zero. Therefore, the ale of each ata pot ca be repreete by the followg eqato. - -, =...6 Th expreo, howeer, lacg two coto eee to ole for the + cotrol pot. Thee coto, ow a the cre e coto, typcally are expree term of a zero cratre or a tagecy coto. Hece, the cotrol pot ca be fo by olg the followg ytem of eqato a how Eqato.7: S = D.7 coto e coto e e e

22 where, S = Data pot = ba fcto ale at the ot D = cotrol pot Srface ero lghtly more complex tha cre ero a ole olg for the rectaglar array of cotrol pot that terpolate to moel ata pot wth repect to two fferet bae. Th proce ca be ecrbe by the followg Eqato.8: S = D T.8 where S repreet the array of ata pot a e coto both recto. repreet the ba fcto matrx of the form Eqato.7 a a fcto of. repreet the ba fcto matrx wth repect to. D the array of cotrol pot to be ole for. I Flemg approach to b-ple ero, the cocept of ot mltplcty employe. Kot mltplcty amot to ag extra ot at pot where the cotty ha to be chage. For tace, orer to ere taget cotty, oe extra ot reqre at the pecfe pot. If tea a harp corer ee to be moele, the reqre ot mltplcty hol be three two extra ot hol be ae to proe wth pot or C cotty at that corer. Parametrc B-ple

23 Each tme a ot ae, the cotty at that pot rece. Howeer, the meo of the cre chage a a ew ba fcto create. Se a ew ba fcto troce, the mber of cotrol pot to be ole for alo creae whch tr creae the ee for a extra cotrat orer to ole for the ew cotrol pot the ero proce. Thee extra cotrat ca be proe term of tagecy coto or taget ector. For each mltple ot ae to the ot eqece, a taget ector cotrat ca be ae to the lear ytem orer to ole for the extra cotrol pot. Th, for C cotty, oe taget ector reqre, wherea for C cotty, two taget ector are reqre; oe o ether e of the ata pot repreetg the abrpt chage tagecy. Fgre.8 how the effect ag mltple ot ha o the B-ple ba. Whe g cotty cotrat, a ere of tep hae to tae place. Frt, the ata pot are parametrze wth oe of the aalable techqe form, chor legth, etc.. ext, ot mltplcty ae whereer cotty cotrat are reqre. Oce a ew et of ot efe, all ba fcto are calclate o that lear ytem clg cotty cotrat ca be aemble a ole. Parametrc B-ple

24 Fgre.8: Effect of ag mltple ot o the B-ple ba [Flem9a]. Parametrc B-ple

1. Linear second-order circuits

1. Linear second-order circuits ear eco-orer crcut Sere R crcut Dyamc crcut cotag two capactor or two uctor or oe uctor a oe capactor are calle the eco orer crcut At frt we coer a pecal cla of the eco-orer crcut, amely a ere coecto of

More information

B-spline curves. 1. Properties of the B-spline curve. control of the curve shape as opposed to global control by using a special set of blending

B-spline curves. 1. Properties of the B-spline curve. control of the curve shape as opposed to global control by using a special set of blending B-sple crve Copyrght@, YZU Optmal Desg Laboratory. All rghts reserved. Last pdated: Yeh-Lag Hs (--9). ote: Ths s the corse materal for ME Geometrc modelg ad compter graphcs, Ya Ze Uversty. art of ths materal

More information

Trignometric Inequations and Fuzzy Information Theory

Trignometric Inequations and Fuzzy Information Theory Iteratoal Joural of Scetfc ad Iovatve Mathematcal Reearch (IJSIMR) Volume, Iue, Jauary - 0, PP 00-07 ISSN 7-07X (Prt) & ISSN 7- (Ole) www.arcjoural.org Trgometrc Iequato ad Fuzzy Iformato Theory P.K. Sharma,

More information

Chapter Newton-Raphson Method of Solving Simultaneous Nonlinear Equations

Chapter Newton-Raphson Method of Solving Simultaneous Nonlinear Equations Chapter 7 Newto-Rapho Method o Solg Smltaeo Nolear Eqato Ater readg th chapter o hold be able to: dere the Newto-Rapho method ormla or mltaeo olear eqato deelop the algorthm o the Newto-Rapho method or

More information

An Expansion of the Derivation of the Spline Smoothing Theory Alan Kaylor Cline

An Expansion of the Derivation of the Spline Smoothing Theory Alan Kaylor Cline A Epaso of the Derato of the Sple Smoothg heory Ala Kaylor Cle he classc paper "Smoothg by Sple Fctos", Nmersche Mathematk 0, 77-83 967) by Chrsta Resch showed that atral cbc sples were the soltos to a

More information

Solutions to Odd-Numbered End-of-Chapter Exercises: Chapter 17

Solutions to Odd-Numbered End-of-Chapter Exercises: Chapter 17 Itroucto to Ecoometrcs (3 r Upate Eto) by James H. Stock a Mark W. Watso Solutos to O-Numbere E-of-Chapter Exercses: Chapter 7 (Ths erso August 7, 04) 05 Pearso Eucato, Ic. Stock/Watso - Itroucto to Ecoometrcs

More information

Collapsing to Sample and Remainder Means. Ed Stanek. In order to collapse the expanded random variables to weighted sample and remainder

Collapsing to Sample and Remainder Means. Ed Stanek. In order to collapse the expanded random variables to weighted sample and remainder Collapg to Saple ad Reader Mea Ed Staek Collapg to Saple ad Reader Average order to collape the expaded rado varable to weghted aple ad reader average, we pre-ultpled by ( M C C ( ( M C ( M M M ( M M M,

More information

Five-axis Spline Interpolation Algorithm for Digital Manufacturing System

Five-axis Spline Interpolation Algorithm for Digital Manufacturing System 3r Iteratoal Coferece o Mechatrocs, Robotcs a Atomato (ICMRA 25 Fve-axs Sple Iterpolato Algorthm for Dgtal Mafactrg System LI Hyg, a a CHE Lagj 2,b * Zhegzho Isttte of Aeroatcal Istry Maagemet, Cha 2 Zhegzho

More information

UNIT 7 RANK CORRELATION

UNIT 7 RANK CORRELATION UNIT 7 RANK CORRELATION Rak Correlato Structure 7. Itroucto Objectves 7. Cocept of Rak Correlato 7.3 Dervato of Rak Correlato Coeffcet Formula 7.4 Te or Repeate Raks 7.5 Cocurret Devato 7.6 Summar 7.7

More information

Linear Approximating to Integer Addition

Linear Approximating to Integer Addition Lear Approxmatg to Iteger Addto L A-Pg Bejg 00085, P.R. Cha apl000@a.com Abtract The teger addto ofte appled cpher a a cryptographc mea. I th paper we wll preet ome reult about the lear approxmatg for

More information

FORCED TRANSVERSE VIBRATIONS OF ELASTIC BEAMS AND THEIR DYNAMIC ABSORPTION

FORCED TRANSVERSE VIBRATIONS OF ELASTIC BEAMS AND THEIR DYNAMIC ABSORPTION FORCED RANSVERSE VIBRAIONS OF ELASIC BEAMS AND HR DYNAMIC ABSORPION. Itrocto Srboljb S. Smć Vlamr M. Mško It ell ko that orce brato o oe-egree-o-reeom yamcal ytem caot be ampe by mea o orary co amper.

More information

L5 Polynomial / Spline Curves

L5 Polynomial / Spline Curves L5 Polyomal / Sple Curves Cotets Coc sectos Polyomal Curves Hermte Curves Bezer Curves B-Sples No-Uform Ratoal B-Sples (NURBS) Mapulato ad Represetato of Curves Types of Curve Equatos Implct: Descrbe a

More information

CS473-Algorithms I. Lecture 12b. Dynamic Tables. CS 473 Lecture X 1

CS473-Algorithms I. Lecture 12b. Dynamic Tables. CS 473 Lecture X 1 CS473-Algorthm I Lecture b Dyamc Table CS 473 Lecture X Why Dyamc Table? I ome applcato: We do't kow how may object wll be tored a table. We may allocate pace for a table But, later we may fd out that

More information

Graphs and graph models-graph terminology and special types of graphs-representing graphs and graph isomorphism -connectivity-euler and Hamilton

Graphs and graph models-graph terminology and special types of graphs-representing graphs and graph isomorphism -connectivity-euler and Hamilton Prepare by Dr. A.R.VIJAYALAKSHMI Graphs a graph moels-graph termology a specal types of graphs-represetg graphs a graph somorphsm -coectty-euler a Hamlto paths Graph Graph: A graph G = (V, E) cossts of

More information

Signal Recovery - Prof. S. Cova - Exam 2016/02/16 - P1 pag.1

Signal Recovery - Prof. S. Cova - Exam 2016/02/16 - P1 pag.1 gal Recovery - Pro.. Cova - Exam 06/0/6 - P pag. PROBEM Data ad Note Appled orce F rt cae: tep ple ecod cae: rectaglar ple wth drato p = 5m Pezoelectrc orce eor A q =0pC/N orce-to-charge covero C = 500pF

More information

Curves - Foundation of Free-form Surfaces

Curves - Foundation of Free-form Surfaces //9 Cres - Fodato of Free-form Srfaces Why Stdy Cres? Cres are the bascs for srfaces Whe asked to modfy a partclar etty o a CAD system, kowledge of the ettes ca crease yor prodctty Uderstad how the math

More information

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K

ROOT-LOCUS ANALYSIS. Lecture 11: Root Locus Plot. Consider a general feedback control system with a variable gain K. Y ( s ) ( ) K ROOT-LOCUS ANALYSIS Coder a geeral feedback cotrol yte wth a varable ga. R( Y( G( + H( Root-Locu a plot of the loc of the pole of the cloed-loop trafer fucto whe oe of the yte paraeter ( vared. Root locu

More information

CS5620 Intro to Computer Graphics

CS5620 Intro to Computer Graphics CS56 Itro to Computer Graphcs Geometrc Modelg art II Geometrc Modelg II hyscal Sples Curve desg pre-computers Cubc Sples Stadard sple put set of pots { } =, No dervatves specfed as put Iterpolate by cubc

More information

Reaction Time VS. Drug Percentage Subject Amount of Drug Times % Reaction Time in Seconds 1 Mary John Carl Sara William 5 4

Reaction Time VS. Drug Percentage Subject Amount of Drug Times % Reaction Time in Seconds 1 Mary John Carl Sara William 5 4 CHAPTER Smple Lear Regreo EXAMPLE A expermet volvg fve ubject coducted to determe the relatohp betwee the percetage of a certa drug the bloodtream ad the legth of tme t take the ubject to react to a tmulu.

More information

n -dimensional vectors follow naturally from the one

n -dimensional vectors follow naturally from the one B. Vectors ad sets B. Vectors Ecoomsts study ecoomc pheomea by buldg hghly stylzed models. Uderstadg ad makg use of almost all such models requres a hgh comfort level wth some key mathematcal sklls. I

More information

3 Stress and the Balance Principles

3 Stress and the Balance Principles Stre a the Balace Prcple hree bac law of phyc are cue th Chapter: () he Law of Coerato of Ma () he Balace of Lear Mometum () he Balace of Agular Mometum together wth the coerato of mechacal eergy a the

More information

Layered structures: transfer matrix formalism

Layered structures: transfer matrix formalism Layered tructure: trafer matrx formalm Iterface betwee LI meda Trafer matrx formalm Petr Kužel Practcally oly oe formula to be kow order to calculate ay tructure Applcato: Atreflectve coatg Delectrc mrror,

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

International Journal of Pure and Applied Sciences and Technology

International Journal of Pure and Applied Sciences and Technology It J Pure Appl Sc Techol, () (00), pp 79-86 Iteratoal Joural of Pure ad Appled Scece ad Techology ISSN 9-607 Avalable ole at wwwjopaaat Reearch Paper Some Stroger Chaotc Feature of the Geeralzed Shft Map

More information

Computer Graphics. Geometric Modeling. Geometric Modeling. Page. Copyright Gotsman, Elber, Barequet, Karni, Sheffer Computer Science - Technion

Computer Graphics. Geometric Modeling. Geometric Modeling. Page. Copyright Gotsman, Elber, Barequet, Karni, Sheffer Computer Science - Technion Computer Graphcs Geometrc Modelg Geometrc Modelg A Example 4 Outle Objectve: Develop methods ad algorthms to mathematcally model shape of real world objects Categores: Wre-Frame Represetato Object s represeted

More information

Computational Geometry

Computational Geometry Problem efto omputatoal eometry hapter 6 Pot Locato Preprocess a plaar map S. ve a query pot p, report the face of S cotag p. oal: O()-sze data structure that eables O(log ) query tme. pplcato: Whch state

More information

( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix.

( ) ( ) ( ( )) ( ) ( ) ( ) ( ) ( ) = ( ) ( ) + ( ) ( ) = ( ( )) ( ) + ( ( )) ( ) Review. Second Derivatives for f : y R. Let A be an m n matrix. Revew + v, + y = v, + v, + y, + y, Cato! v, + y, + v, + y geeral Let A be a atr Let f,g : Ω R ( ) ( ) R y R Ω R h( ) f ( ) g ( ) ( ) ( ) ( ( )) ( ) dh = f dg + g df A, y y A Ay = = r= c= =, : Ω R he Proof

More information

Geometric Modeling

Geometric Modeling Geometrc Modelg 9.580.0 Crves Morteso Chater -5 ad Agel Chater 9 Crve Bascs Crve: Locs of a ot movg wth degree of freedom. Some tyes of eqatos to descrbe crves: Itrsc o relace o exteral frame of referece

More information

C.11 Bang-bang Control

C.11 Bang-bang Control Itroucto to Cotrol heory Iclug Optmal Cotrol Nguye a e -.5 C. Bag-bag Cotrol. Itroucto hs chapter eals wth the cotrol wth restrctos: s boue a mght well be possble to have scotutes. o llustrate some of

More information

Simple Linear Regression Analysis

Simple Linear Regression Analysis LINEAR REGREION ANALYSIS MODULE II Lecture - 5 Smple Lear Regreo Aaly Dr Shalabh Departmet of Mathematc Stattc Ida Ittute of Techology Kapur Jot cofdece rego for A jot cofdece rego for ca alo be foud Such

More information

Generalized Linear Regression with Regularization

Generalized Linear Regression with Regularization Geeralze Lear Regresso wth Regularzato Zoya Bylsk March 3, 05 BASIC REGRESSION PROBLEM Note: I the followg otes I wll make explct what s a vector a what s a scalar usg vec t or otato, to avo cofuso betwee

More information

Camera calibration & radiometry

Camera calibration & radiometry Caera calbrato & radoetr Readg: Chapter 2, ad secto 5.4, Forsth & oce Chapter, Hor Optoal readg: Chapter 4, Forsth & oce Sept. 2, 22 MI 6.8/6.866 rofs. Freea ad Darrell Req: F 2, 5.4, H Opt: F 4 Req: F

More information

Log1 Contest Round 2 Theta Complex Numbers. 4 points each. 5 points each

Log1 Contest Round 2 Theta Complex Numbers. 4 points each. 5 points each 01 Log1 Cotest Roud Theta Complex Numbers 1 Wrte a b Wrte a b form: 1 5 form: 1 5 4 pots each Wrte a b form: 65 4 4 Evaluate: 65 5 Determe f the followg statemet s always, sometmes, or ever true (you may

More information

The Topological Indices of some Dendrimer Graphs

The Topological Indices of some Dendrimer Graphs Iraa J Math Chem 8 March 7 5 5 Iraa Joral of Mathematcal Chemstry Joral homepage: wwwjmckashaacr The Topologcal Ices of some Dermer Graphs M R DARASHEH a M NAMDARI b AND S SHOKROLAHI b a School of Mathematcs

More information

Hamilton s principle for non-holonomic systems

Hamilton s principle for non-holonomic systems Das Hamltosche Przp be chtholoome Systeme, Math. A. (935), pp. 94-97. Hamlto s prcple for o-holoomc systems by Georg Hamel Berl Traslate by: D. H. Delphech I the paper Le prcpe e Hamlto et l holoomsme,

More information

2.160 System Identification, Estimation, and Learning Lecture Notes No. 17 April 24, 2006

2.160 System Identification, Estimation, and Learning Lecture Notes No. 17 April 24, 2006 .6 System Idetfcato, Estmato, ad Learg Lectre Notes No. 7 Aprl 4, 6. Iformatve Expermets. Persstece of Exctato Iformatve data sets are closely related to Persstece of Exctato, a mportat cocept sed adaptve

More information

u(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )):

u(x, t) = u 0 (x ct). This Riemann invariant u is constant along characteristics λ with x = x 0 +ct (u(x, t) = u 0 (x 0 )): x, t, h x The Frst-Order Wave Eqato The frst-order wave advecto eqato s c > 0 t + c x = 0, x, t = 0 = 0x. The solto propagates the tal data 0 to the rght wth speed c: x, t = 0 x ct. Ths Rema varat s costat

More information

LINEARLY CONSTRAINED MINIMIZATION BY USING NEWTON S METHOD

LINEARLY CONSTRAINED MINIMIZATION BY USING NEWTON S METHOD Jural Karya Asl Loreka Ahl Matematk Vol 8 o 205 Page 084-088 Jural Karya Asl Loreka Ahl Matematk LIEARLY COSTRAIED MIIMIZATIO BY USIG EWTO S METHOD Yosza B Dasrl, a Ismal B Moh 2 Faculty Electrocs a Computer

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

Motion Estimation Based on Unit Quaternion Decomposition of the Rotation Matrix

Motion Estimation Based on Unit Quaternion Decomposition of the Rotation Matrix Moto Estmato Based o Ut Qatero Decomposto of the Rotato Matrx Hag Y Ya Baozog (Isttte of Iformato Scece orther Jaotog Uversty Bejg 00044 PR Cha Abstract Based o the t qatero decomposto of rotato matrx

More information

Minimal Surfaces and Gauss Curvature of Conoid in Finsler Spaces with (α, β)-metrics *

Minimal Surfaces and Gauss Curvature of Conoid in Finsler Spaces with (α, β)-metrics * Advace Pre Mathematc -5 http://ddoorg/6/apm Plhed Ole Jly (http://wwwscrporg/joral/apm) Mmal Srface ad Ga Crvatre of Cood Fler Space wth (α β)-metrc Dghe Xe Q He Departmet of Mathematc Togj Uverty Shagha

More information

ON THE CHROMATIC NUMBER OF GENERALIZED STABLE KNESER GRAPHS

ON THE CHROMATIC NUMBER OF GENERALIZED STABLE KNESER GRAPHS ON THE CHROMATIC NUMBER OF GENERALIZED STABLE KNESER GRAPHS JAKOB JONSSON Abstract. For each teger trple (, k, s) such that k 2, s 2, a ks, efe a graph the followg maer. The vertex set cossts of all k-subsets

More information

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

Lecture 5: Interpolation. Polynomial interpolation Rational approximation

Lecture 5: Interpolation. Polynomial interpolation Rational approximation Lecture 5: Iterpolato olyomal terpolato Ratoal appromato Coeffcets of the polyomal Iterpolato: Sometme we kow the values of a fucto f for a fte set of pots. Yet we wat to evaluate f for other values perhaps

More information

Instituto Tecnológico de Aeronáutica FINITE ELEMENTS I. Class notes AE-245

Instituto Tecnológico de Aeronáutica FINITE ELEMENTS I. Class notes AE-245 Isttto Tecológco de Aeroátca FIITE ELEETS I Class otes AE-45 Isttto Tecológco de Aeroátca 8. Beams ad Plates AE-45 Isttto Tecológco de Aeroátca BEAS AD PLATES Itrodcto Eler-Beroll beam model ad Krcoff

More information

Maximum Walk Entropy Implies Walk Regularity

Maximum Walk Entropy Implies Walk Regularity Maxmum Walk Etropy Imples Walk Regularty Eresto Estraa, a José. e la Peña Departmet of Mathematcs a Statstcs, Uversty of Strathclye, Glasgow G XH, U.K., CIMT, Guaajuato, Mexco BSTRCT: The oto of walk etropy

More information

PTAS for Bin-Packing

PTAS for Bin-Packing CS 663: Patter Matchg Algorthms Scrbe: Che Jag /9/00. Itroducto PTAS for B-Packg The B-Packg problem s NP-hard. If we use approxmato algorthms, the B-Packg problem could be solved polyomal tme. For example,

More information

MA 524 Homework 6 Solutions

MA 524 Homework 6 Solutions MA 524 Homework 6 Solutos. Sce S(, s the umber of ways to partto [] to k oempty blocks, ad c(, s the umber of ways to partto to k oempty blocks ad also the arrage each block to a cycle, we must have S(,

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

Basic Structures: Sets, Functions, Sequences, and Sums

Basic Structures: Sets, Functions, Sequences, and Sums ac Structure: Set, Fucto, Sequece, ad Sum CSC-9 Dcrete Structure Kotat uch - LSU Set et a uordered collecto o object Eglh alphabet vowel: V { a, e,, o, u} a V b V Odd potve teger le tha : elemet o et member

More information

Effects of thin film thickness on emittance, reflectance and transmittance of nano scale multilayers

Effects of thin film thickness on emittance, reflectance and transmittance of nano scale multilayers Iteratoal Joural of the Phycal Scece Vol. 5(5), pp. 465-469, May 0 Avalable ole at http://www.acaemcjoural.org/ijps ISSN 199-1950 0 Acaemc Joural Full Legth Reearch Paper Effect of th flm thcke o emttace,

More information

USING MORE ACCURATE STRAIN FOR THREE-DIMENSIONAL TRUSS ANALYSIS

USING MORE ACCURATE STRAIN FOR THREE-DIMENSIONAL TRUSS ANALYSIS ASIA JOURAL OF CIVIL EGIEERIG (BHRC VOL. 7, O. (6 PAGES 7-6 USIG MORE ACCURAE SRAI FOR HREE-DIMESIOAL RUSS AALYSIS M. Rezaee-Paja a R. asera Departmet of Cl Egeerg, Feros Uersty of Mashha, Mashha, Ira

More information

Third handout: On the Gini Index

Third handout: On the Gini Index Thrd hadout: O the dex Corrado, a tala statstca, proposed (, 9, 96) to measure absolute equalt va the mea dfferece whch s defed as ( / ) where refers to the total umber of dvduals socet. Assume that. The

More information

Fig. 1: Streamline coordinates

Fig. 1: Streamline coordinates 1 Equatio of Motio i Streamlie Coordiate Ai A. Soi, MIT 2.25 Advaced Fluid Mechaic Euler equatio expree the relatiohip betwee the velocity ad the preure field i ivicid flow. Writte i term of treamlie coordiate,

More information

MATH 247/Winter Notes on the adjoint and on normal operators.

MATH 247/Winter Notes on the adjoint and on normal operators. MATH 47/Wter 00 Notes o the adjot ad o ormal operators I these otes, V s a fte dmesoal er product space over, wth gve er * product uv, T, S, T, are lear operators o V U, W are subspaces of V Whe we say

More information

Chapter 9 Jordan Block Matrices

Chapter 9 Jordan Block Matrices Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.

More information

Quiz 1- Linear Regression Analysis (Based on Lectures 1-14)

Quiz 1- Linear Regression Analysis (Based on Lectures 1-14) Quz - Lear Regreo Aaly (Baed o Lecture -4). I the mple lear regreo model y = β + βx + ε, wth Tme: Hour Ε ε = Ε ε = ( ) 3, ( ), =,,...,, the ubaed drect leat quare etmator ˆβ ad ˆβ of β ad β repectvely,

More information

( x) min. Nonlinear optimization problem without constraints NPP: then. Global minimum of the function f(x)

( x) min. Nonlinear optimization problem without constraints NPP: then. Global minimum of the function f(x) Objectve fucto f() : he optzato proble cossts of fg a vector of ecso varables belogg to the feasble set of solutos R such that It s eote as: Nolear optzato proble wthout costrats NPP: R f ( ) : R R f f

More information

Taylor s Series and Interpolation. Interpolation & Curve-fitting. CIS Interpolation. Basic Scenario. Taylor Series interpolates at a specific

Taylor s Series and Interpolation. Interpolation & Curve-fitting. CIS Interpolation. Basic Scenario. Taylor Series interpolates at a specific CIS 54 - Iterpolato Roger Crawfs Basc Scearo We are able to prod some fucto, but do ot kow what t really s. Ths gves us a lst of data pots: [x,f ] f(x) f f + x x + August 2, 25 OSU/CIS 54 3 Taylor s Seres

More information

Lecture 3 Probability review (cont d)

Lecture 3 Probability review (cont d) STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto

More information

Some distances and sequences in a weighted graph

Some distances and sequences in a weighted graph IOSR Joural of Mathematc (IOSR-JM) e-issn: 78-578 p-issn: 19 765X PP 7-15 wwworjouralorg Some dtace ad equece a weghted graph Jll K Mathew 1, Sul Mathew Departmet of Mathematc Federal Ittute of Scece ad

More information

= 2. Statistic - function that doesn't depend on any of the known parameters; examples:

= 2. Statistic - function that doesn't depend on any of the known parameters; examples: of Samplg Theory amples - uemploymet househol cosumpto survey Raom sample - set of rv's... ; 's have ot strbuto [ ] f f s vector of parameters e.g. Statstc - fucto that oes't epe o ay of the ow parameters;

More information

11. Ideal Gas Mixture

11. Ideal Gas Mixture . Ideal Ga xture. Geeral oderato ad xture of Ideal Gae For a geeral xture of N opoet, ea a pure ubtae [kg ] te a for ea opoet. [kol ] te uber of ole for ea opoet. e al a ( ) [kg ] N e al uber of ole (

More information

TESTS BASED ON MAXIMUM LIKELIHOOD

TESTS BASED ON MAXIMUM LIKELIHOOD ESE 5 Toy E. Smth. The Basc Example. TESTS BASED ON MAXIMUM LIKELIHOOD To llustrate the propertes of maxmum lkelhood estmates ad tests, we cosder the smplest possble case of estmatg the mea of the ormal

More information

On Eccentricity Sum Eigenvalue and Eccentricity Sum Energy of a Graph

On Eccentricity Sum Eigenvalue and Eccentricity Sum Energy of a Graph Aals of Pure ad Appled Mathematcs Vol. 3, No., 7, -3 ISSN: 79-87X (P, 79-888(ole Publshed o 3 March 7 www.researchmathsc.org DOI: http://dx.do.org/.7/apam.3a Aals of O Eccetrcty Sum Egealue ad Eccetrcty

More information

A unified matrix representation for degree reduction of Bézier curves

A unified matrix representation for degree reduction of Bézier curves Computer Aded Geometrc Desg 21 2004 151 164 wwwelsevercom/locate/cagd A ufed matrx represetato for degree reducto of Bézer curves Hask Suwoo a,,1, Namyog Lee b a Departmet of Mathematcs, Kokuk Uversty,

More information

On the energy of complement of regular line graphs

On the energy of complement of regular line graphs MATCH Coucato Matheatcal ad Coputer Chetry MATCH Cou Math Coput Che 60 008) 47-434 ISSN 0340-653 O the eergy of copleet of regular le graph Fateeh Alaghpour a, Baha Ahad b a Uverty of Tehra, Tehra, Ira

More information

Lattices. Mathematical background

Lattices. Mathematical background Lattces Mathematcal backgroud Lattces : -dmesoal Eucldea space. That s, { T x } x x = (,, ) :,. T T If x= ( x,, x), y = ( y,, y), the xy, = xy (er product of xad y) x = /2 xx, (Eucldea legth or orm of

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

More information

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II CEE49b Chapter - Free Vbrato of Mult-Degree-of-Freedom Systems - II We ca obta a approxmate soluto to the fudametal atural frequecy through a approxmate formula developed usg eergy prcples by Lord Raylegh

More information

Transforms that are commonly used are separable

Transforms that are commonly used are separable Trasforms s Trasforms that are commoly used are separable Eamples: Two-dmesoal DFT DCT DST adamard We ca the use -D trasforms computg the D separable trasforms: Take -D trasform of the rows > rows ( )

More information

Ideal multigrades with trigonometric coefficients

Ideal multigrades with trigonometric coefficients Ideal multgrades wth trgoometrc coeffcets Zarathustra Brady December 13, 010 1 The problem A (, k) multgrade s defed as a par of dstct sets of tegers such that (a 1,..., a ; b 1,..., b ) a j = =1 for all

More information

On the convergence of derivatives of Bernstein approximation

On the convergence of derivatives of Bernstein approximation O the covergece of dervatves of Berste approxmato Mchael S. Floater Abstract: By dfferetatg a remader formula of Stacu, we derve both a error boud ad a asymptotc formula for the dervatves of Berste approxmato.

More information

Application of Legendre Bernstein basis transformations to degree elevation and degree reduction

Application of Legendre Bernstein basis transformations to degree elevation and degree reduction Computer Aded Geometrc Desg 9 79 78 www.elsever.com/locate/cagd Applcato of Legedre Berste bass trasformatos to degree elevato ad degree reducto Byug-Gook Lee a Yubeom Park b Jaechl Yoo c a Dvso of Iteret

More information

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation PGE 30: Formulato ad Soluto Geosystems Egeerg Dr. Balhoff Iterpolato Numercal Methods wth MATLAB, Recktewald, Chapter 0 ad Numercal Methods for Egeers, Chapra ad Caale, 5 th Ed., Part Fve, Chapter 8 ad

More information

Review Exam II Complex Analysis

Review Exam II Complex Analysis Revew Exam II Complex Aalyss Uderled Propostos or Theorems: Proofs May Be Asked for o Exam Chapter 3. Ifte Seres Defto: Covergece Defto: Absolute Covergece Proposto. Absolute Covergece mples Covergece

More information

Power Flow S + Buses with either or both Generator Load S G1 S G2 S G3 S D3 S D1 S D4 S D5. S Dk. Injection S G1

Power Flow S + Buses with either or both Generator Load S G1 S G2 S G3 S D3 S D1 S D4 S D5. S Dk. Injection S G1 ower Flow uses wth ether or both Geerator Load G G G D D 4 5 D4 D5 ecto G Net Comple ower ecto - D D ecto s egatve sg at load bus = _ G D mlarl Curret ecto = G _ D At each bus coservato of comple power

More information

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions. Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos

More information

Chapter 3. Differentiation 3.3 Differentiation Rules

Chapter 3. Differentiation 3.3 Differentiation Rules 3.3 Dfferetato Rules 1 Capter 3. Dfferetato 3.3 Dfferetato Rules Dervatve of a Costat Fucto. If f as te costat value f(x) = c, te f x = [c] = 0. x Proof. From te efto: f (x) f(x + ) f(x) o c c 0 = 0. QED

More information

1 Onto functions and bijections Applications to Counting

1 Onto functions and bijections Applications to Counting 1 Oto fuctos ad bectos Applcatos to Coutg Now we move o to a ew topc. Defto 1.1 (Surecto. A fucto f : A B s sad to be surectve or oto f for each b B there s some a A so that f(a B. What are examples of

More information

Nuclear and Particle Physics - Lecture 16 Neutral kaon decays and oscillations

Nuclear and Particle Physics - Lecture 16 Neutral kaon decays and oscillations 1 Introction Nclear an Particle Phyic - Lectre 16 Netral kaon ecay an ocillation e have alreay een that the netral kaon will have em-leptonic an haronic ecay. However, they alo exhibit the phenomenon of

More information

Econometric Methods. Review of Estimation

Econometric Methods. Review of Estimation Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

More information

III-16 G. Brief Review of Grand Orthogonality Theorem and impact on Representations (Γ i ) l i = h n = number of irreducible representations.

III-16 G. Brief Review of Grand Orthogonality Theorem and impact on Representations (Γ i ) l i = h n = number of irreducible representations. III- G. Bref evew of Grad Orthogoalty Theorem ad mpact o epresetatos ( ) GOT: h [ () m ] [ () m ] δδ δmm ll GOT puts great restrcto o form of rreducble represetato also o umber: l h umber of rreducble

More information

We have already referred to a certain reaction, which takes place at high temperature after rich combustion.

We have already referred to a certain reaction, which takes place at high temperature after rich combustion. ME 41 Day 13 Topcs Chemcal Equlbrum - Theory Chemcal Equlbrum Example #1 Equlbrum Costats Chemcal Equlbrum Example #2 Chemcal Equlbrum of Hot Bured Gas 1. Chemcal Equlbrum We have already referred to a

More information

4 Inner Product Spaces

4 Inner Product Spaces 11.MH1 LINEAR ALGEBRA Summary Notes 4 Ier Product Spaces Ier product s the abstracto to geeral vector spaces of the famlar dea of the scalar product of two vectors or 3. I what follows, keep these key

More information

The Quark Model. Introduction to Elementary Particle Physics. Diego Bettoni Anno Accademico

The Quark Model. Introduction to Elementary Particle Physics. Diego Bettoni Anno Accademico The Qark Moel trocto to Eleetary Partcle Phyc Dego Betto Ao Accaeco - Otle yetre a grop overvew The flavor yetry q q tate: eo Peocalar a vector eo Zweg rle q q q tate: baryo Color Haro ae a agetc oet yetre

More information

Section l h l Stem=Tens. 8l Leaf=Ones. 8h l 03. 9h 58

Section l h l Stem=Tens. 8l Leaf=Ones. 8h l 03. 9h 58 Secto.. 6l 34 6h 667899 7l 44 7h Stem=Tes 8l 344 Leaf=Oes 8h 5557899 9l 3 9h 58 Ths dsplay brgs out the gap the data: There are o scores the hgh 7's. 6. a. beams cylders 9 5 8 88533 6 6 98877643 7 488

More information

REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION

REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION REVIEW OF SIMPLE LINEAR REGRESSION SIMPLE LINEAR REGRESSION I lear regreo, we coder the frequecy dtrbuto of oe varable (Y) at each of everal level of a ecod varable (X). Y kow a the depedet varable. The

More information

d λ Marko ŠLJIVARIĆ, Milan REZO, Ilija GRGIĆ 1 DISTORTION MODELLING (INTRODUCTION)

d λ Marko ŠLJIVARIĆ, Milan REZO, Ilija GRGIĆ 1 DISTORTION MODELLING (INTRODUCTION) ISSN 0-6 (Prt ISSN 88-69 (Ole https://o.org/0.79/tv-060780 Orgal scetfc paper Methos of Moellg the Dstorto ase by Dfferet Amot a Oretato of oorate orrectos betwee Two oorate Systems at Varos Locatos Maro

More information

UNIT 6 CORRELATION COEFFICIENT

UNIT 6 CORRELATION COEFFICIENT UNIT CORRELATION COEFFICIENT Correlato Coeffcet Structure. Itroucto Objectves. Cocept a Defto of Correlato.3 Tpes of Correlato.4 Scatter Dagram.5 Coeffcet of Correlato Assumptos for Correlato Coeffcet.

More information

Mean is only appropriate for interval or ratio scales, not ordinal or nominal.

Mean is only appropriate for interval or ratio scales, not ordinal or nominal. Mea Same as ordary average Sum all the data values ad dvde by the sample sze. x = ( x + x +... + x Usg summato otato, we wrte ths as x = x = x = = ) x Mea s oly approprate for terval or rato scales, ot

More information

Alternating Direction Implicit Method

Alternating Direction Implicit Method Alteratg Drecto Implct Method Whle dealg wth Ellptc Eqatos the Implct form the mber of eqatos to be solved are N M whch are qte large mber. Thogh the coeffcet matrx has may zeros bt t s ot a baded system.

More information

Lecture 9: Tolerant Testing

Lecture 9: Tolerant Testing Lecture 9: Tolerat Testg Dael Kae Scrbe: Sakeerth Rao Aprl 4, 07 Abstract I ths lecture we prove a quas lear lower boud o the umber of samples eeded to do tolerat testg for L dstace. Tolerat Testg We have

More information

Given a table of data poins of an unknown or complicated function f : we want to find a (simpler) function p s.t. px (

Given a table of data poins of an unknown or complicated function f : we want to find a (simpler) function p s.t. px ( Iterpolato 1 Iterpolato Gve a table of data pos of a ukow or complcated fucto f : y 0 1 2 y y y y 0 1 2 we wat to fd a (smpler) fucto p s.t. p ( ) = y for = 0... p s sad to terpolate the table or terpolate

More information

Lecture 25 Highlights Phys 402

Lecture 25 Highlights Phys 402 Lecture 5 Hhlht Phy 40 e are ow o to coder the tattcal mechac of quatum ytem. I partcular we hall tudy the macrocopc properte of a collecto of may (N ~ 0 detcal ad dtuhable Fermo ad Boo wth overlapp wavefucto.

More information

Theory study about quarter-wave-stack dielectric mirrors

Theory study about quarter-wave-stack dielectric mirrors Theor tud about quarter-wave-tack delectrc rror Stratfed edu tratted reflected reflected Stratfed edu tratted cdet cdet T T Frt, coder a wave roagato a tratfed edu. A we kow, a arbtrarl olared lae wave

More information

UNIT 2 SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS

UNIT 2 SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS Numercal Computg -I UNIT SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS Structure Page Nos..0 Itroducto 6. Objectves 7. Ital Approxmato to a Root 7. Bsecto Method 8.. Error Aalyss 9.4 Regula Fals Method

More information

Maps on Triangular Matrix Algebras

Maps on Triangular Matrix Algebras Maps o ragular Matrx lgebras HMED RMZI SOUROUR Departmet of Mathematcs ad Statstcs Uversty of Vctora Vctora, BC V8W 3P4 CND sourour@mathuvcca bstract We surveys results about somorphsms, Jorda somorphsms,

More information