Transformations are used: Transformations. Simple Transformations. Rigid-Body / Euclidean Transforms. Similitudes / Similarity Transforms

Size: px
Start display at page:

Download "Transformations are used: Transformations. Simple Transformations. Rigid-Body / Euclidean Transforms. Similitudes / Similarity Transforms"

Transcription

1 rasormatios are sed: rasormatios Positio ojets i a see modelig) hage the shae o ojets reate mltile oies o ojets Projetio or irtal ameras imatios Ma o the slides are take rom MI EES 6.87, rad ad tler Simle rasormatios igid-od / Elidea rasorms Preseres distaes Preseres agles a e omied re these oeratios iertile? Yes, eet sale igid / Elidea Idetit raslatio Similitdes / Similarit rasorms Liear rasormatios Preseres agles Similitdes igid / Elidea Similitdes igid / Elidea Liear raslatio Idetit Isotroi Salig raslatio Idetit Isotroi Salig Salig eletio Shear

2 Liear rasormatios ie rasormatios L q) L) Lq) La) a L) reseres arallel lies ie Similitdes igid / Elidea Liear Similitdes igid / Elidea Liear raslatio Idetit Isotroi Salig Salig eletio Shear raslatio Idetit Isotroi Salig Salig eletio Shear Projetie rasormatios Persetie Projetio reseres lies Projetie ie Similitdes igid / Elidea Idetit raslatio Liear Salig Isotroi Salig eletio Shear Persetie Otlie ssigmet ea Itro to rasormatios lasses o rasormatios eresetig rasormatios omiig rasormatios hage o Orthoormal asis Ho are rasorms ereseted? a d e a d e M t

3 Homogeeos oordiates dd a etra dimesio i, e se matries I, e se 4 4 matries Eah oit has a etra ale, a e i m j g k o M d h l Homogeeos oordiates Most o the time, ad e a igore it a e i j g k d h l I e mltil a homogeeos oordiate a aie matri, is haged Homogeeos Visaliatio iide to ormalie homogeie) W? Poit at iiit diretio) oordiate Sstems ight-haded oordiate sstem:,, ),, ) 7,, ) 4,, ) 4, 5, ) 8,, ) Let-haded oordiate sstem: rasormatios I homogeeos oordiates, trasormatios are rereseted 44 matries. oit trasormatio is erormed: raslate t, t, t) Wh other ith the etra dimesio? ease o traslatios a e eoded i the matri! raslate,,) a d g e h i t t t t t t

4 Sale s, s, s) Isotroi iorm) salig: s s s s s s Sales,s,s) q q Shearig e a d a d e he hage i eah oordiate is a liear omiatio o all three. rasorms a e ito a geeral aralleleied. ot ais - Zotate ) ot ais: ot ais: - - ot k, k, k), a it etor o a aritrar ais odriges Formla) kk-) kk-)ks kk-)-ks kk-)-ks kk-) kk-)-ks otatek, ) k kk-)ks kk-)-ks kk-) o geerate a rotatio i e hae to sei: ais o rotatio d.o.) amot o rotatio d.o.) Note, the ais asses throgh the origi. here & s 4

5 5 oter-lokise rotatio aot the -ais: ) oter-lokise rotatio aot the -ais: ) oter-lokise rotatio aot the -ais: ) Ierse ) ) omosite s,, ad, a erorm a rotatio aot a ais asg throgh the origi. ot s ot a ritrar is is o rotatio a e loated at a oit: 6 d.o.. he idea: make the ais oiidet ith oe o the oordiate aes ais), rotate, ad the trasorm ak. ssme that the ais asses throgh the oit. Stes: raslate P to the origi. Make the ais oiidet ith the -ais or eamle): otate aot the -ais ito the lae. otate aot the -ais oto the -ais. otate as eeded aot the -ais. l ierse rotatios aot ad. l ierse traslatio. ot a ritrar is

6 ot a ritrar is Otlie ssigmet ea Itro to rasormatios lasses o rasormatios eresetig rasormatios omiig rasormatios hage o Orthoormal asis E F Ho are trasorms omied? Sale the raslate No-ommtatie omositio Sale the raslate: ' S ) S,),) Sale,),),) raslate,),) 5,),),) Sale,),),) raslate,),) 5,) Use matri mltiliatio: ' S ) S S atio: matri mltiliatio is NO ommtatie! raslate the Sale: ' S ) S raslate,) 4,) Sale,),) 6,),),) 8,4) No-ommtatie omositio Sale the raslate: ' S ) S S raslate the Sale: ' S ) S S 6 Otlie ssigmet ea Itro to rasormatios lasses o rasormatios eresetig rasormatios omiig rasormatios hage o Orthoormal asis 6

7 eie o ot Prodt hage o Orthoormal asis a Gie: oordiate rames ad oit,,) Fid:,,) hage o Orthoormal asis hage o Orthoormal asis..... ). ). ). ). ). ). ). ). ). ). ). ). ). ). ) Sstitte ito eqatio or :,,) [ [ [. ). ). ). ). ). ). ). ). ). ). ). ) ] ] ] hage o Orthoormal asis [. ) [. ) [. ) erite: [ [ [. ). ). ). ). ). ). ). ). ). ) ]. ) ]. ) ]. ). ). ) ] ] ] hage o Orthoormal asis [. ) [. ) [. ). ). ). ). ). ). ),,) Eressed i asis:. ). ). ). ). ). ) ] ] ]. ). ). ) 7

8 hage o Orthoormal asis hage o Orthoormal asis. ). ). ). ). ). ). ). ). ) M I matri orm: here:.. et. Whats M -, the ierse?.. M - M hagig oordiate Sstems,, ) M is rotatio matri hose olms are U,V, ad W:,, ),, ),, ) MX U d the ierse M U For the rotatio matri: X rasormig Plaes Plae reresetatio: three o-olliear oits imliit eqatio: P P P 8

9 9 rasormig Plaes Oe a to trasorm a lae is trasormig a three o-olliear oits o the lae. other a is to trasorm the lae eqatio: Gie a trasormatio that trasorms [,,,] to [,,,] id [',',','], sh that: ) ) Ÿ

Coordinate Systems. Things to think about:

Coordinate Systems. Things to think about: Coordiate Sstems There are 3 coordiate sstems that a compter graphics programmer is most cocered with: the Object Coordiate Sstem (OCS), the World Coordiate Sstem (WCS), ad the Camera Coordiate Sstem (CCS).

More information

Elementary Linear Algebra

Elementary Linear Algebra Elemetary Liear Algebra Ato & Rorres th Editio Lectre Set Chapter : Eclidea Vector Spaces Chapter Cotet Vectors i -Space -Space ad -Space Norm Distace i R ad Dot Prodct Orthogoality Geometry of Liear Systems

More information

CS 112 Transformations II. Slide 1

CS 112 Transformations II. Slide 1 CS 112 Trasformatios II Slide 1 Compositio of Trasformatios Example: A poit P is first traslated ad the rotated. Traslatio matrix T, Rotatio Matrix R. After Traslatio: P = TP After Rotatio: P =RP =RTP

More information

too many conditions to check!!

too many conditions to check!! Vector Spaces Aioms of a Vector Space closre Defiitio : Let V be a o empty set of vectors with operatios : i. Vector additio :, v є V + v є V ii. Scalar mltiplicatio: li є V k є V where k is scalar. The,

More information

5.1 Review of Singular Value Decomposition (SVD)

5.1 Review of Singular Value Decomposition (SVD) MGMT 69000: Topics i High-dimesioal Data Aalysis Falll 06 Lecture 5: Spectral Clusterig: Overview (cotd) ad Aalysis Lecturer: Jiamig Xu Scribe: Adarsh Barik, Taotao He, September 3, 06 Outlie Review of

More information

Linear Transformations

Linear Transformations Liear rasformatios 6. Itroductio to Liear rasformatios 6. he Kerel ad Rage of a Liear rasformatio 6. Matrices for Liear rasformatios 6.4 rasitio Matrices ad Similarity 6.5 Applicatios of Liear rasformatios

More information

Principal Component Analysis. Nuno Vasconcelos ECE Department, UCSD

Principal Component Analysis. Nuno Vasconcelos ECE Department, UCSD Priipal Compoet Aalysis Nuo Vasoelos ECE Departmet, UCSD Curse of dimesioality typial observatio i Bayes deisio theory: error ireases whe umber of features is large problem: eve for simple models (e.g.

More information

Image Spaces. What might an image space be

Image Spaces. What might an image space be Image Spaces What might a image space be Map each image to a poit i a space Defie a distace betwee two poits i that space Mabe also a shortest path (morph) We have alread see a simple versio of this, i

More information

Machine Learning Regression I Hamid R. Rabiee [Slides are based on Bishop Book] Spring

Machine Learning Regression I Hamid R. Rabiee [Slides are based on Bishop Book] Spring Machie Learig Regressio I Hamid R. Rabiee [Slides are based o Bishop Book] Sprig 015 http://ce.sharif.edu/courses/93-94//ce717-1 Liear Regressio Liear regressio: ivolves a respose variable ad a sigle predictor

More information

Diagonalization of Quadratic Forms. Recall in days past when you were given an equation which looked like

Diagonalization of Quadratic Forms. Recall in days past when you were given an equation which looked like Diagoalizatio of Qadratic Forms Recall i das past whe o were gie a eqatio which looked like ad o were asked to sketch the set of poits which satisf this eqatio. It was ecessar to complete the sqare so

More information

Two or more points can be used to describe a rigid body. This will eliminate the need to define rotational coordinates for the body!

Two or more points can be used to describe a rigid body. This will eliminate the need to define rotational coordinates for the body! OINTCOORDINATE FORMULATION Two or more poits ca be used to describe a rigid body. This will elimiate the eed to defie rotatioal coordiates for the body i z r i i, j r j j rimary oits: The coordiates of

More information

COORDINATE TRANSFORMATIONS FOR CADASTRAL SURVEYING

COORDINATE TRANSFORMATIONS FOR CADASTRAL SURVEYING COORDINATE TRANSFORMATIONS FOR CADASTRAL SURVEYING R. E. Deaki Shool of Mathematial ad Geospatial Siees, RMIT Uiersit email: rod.deaki@rmit.edu.au Marh 007 ABSTRACT A two-dimesioal (D) oformal trasformatio,

More information

1. Draw a function that is quasi-concave but not concave and explain why.

1. Draw a function that is quasi-concave but not concave and explain why. Solutios to Problem Set 4: Costraied Otimisatio. raw a uctio that is quasi-cocave but ot cocave ad elai wh. ots o ossibilities. The dotted lie shows that the curve draw is ot cocave. More to the oit ou

More information

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j. Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α

More information

Fractals - the ultimate art of mathematics. Adam Kozak

Fractals - the ultimate art of mathematics. Adam Kozak Fratals - the ultimate art of mathematis Adam Koak Outlie What is fratal? Self-similarit dimesio Fratal tpes Iteratio Futio Sstems (IFS) L-sstems Itrodutio to omple umbers Madelbrot sets Julia ad Fatou

More information

Sx [ ] = x must yield a

Sx [ ] = x must yield a Math -b Leture #5 Notes This wee we start with a remider about oordiates of a vetor relative to a basis for a subspae ad the importat speial ase where the subspae is all of R. This freedom to desribe vetors

More information

Solutions 3.2-Page 215

Solutions 3.2-Page 215 Solutios.-Page Problem Fid the geeral solutios i powers of of the differetial equatios. State the reurree relatios ad the guarateed radius of overgee i eah ase. ) Substitutig,, ad ito the differetial equatio

More information

ALGEBRAIC GEOMETRY COURSE NOTES, LECTURE 5: SINGULARITIES.

ALGEBRAIC GEOMETRY COURSE NOTES, LECTURE 5: SINGULARITIES. ALGEBRAIC GEOMETRY COURSE NOTES, LECTURE 5: SINGULARITIES. ANDREW SALCH 1. The Jacobia criterio for osigularity. You have probably oticed by ow that some poits o varieties are smooth i a sese somethig

More information

Orthogonal transformations

Orthogonal transformations Orthogoal trasformatios October 12, 2014 1 Defiig property The squared legth of a vector is give by takig the dot product of a vector with itself, v 2 v v g ij v i v j A orthogoal trasformatio is a liear

More information

Math E-21b Spring 2018 Homework #2

Math E-21b Spring 2018 Homework #2 Math E- Sprig 08 Homework # Prolems due Thursday, Feruary 8: Sectio : y = + 7 8 Fid the iverse of the liear trasformatio [That is, solve for, i terms of y, y ] y = + 0 Cosider the circular face i the accompayig

More information

Partial Differential Equations

Partial Differential Equations EE 84 Matematical Metods i Egieerig Partial Differetial Eqatios Followig are some classical partial differetial eqatios were is assmed to be a fctio of two or more variables t (time) ad y (spatial coordiates).

More information

15.093J Optimization Methods. Lecture 22: Barrier Interior Point Algorithms

15.093J Optimization Methods. Lecture 22: Barrier Interior Point Algorithms 1593J Otimizatio Methods Lecture : Barrier Iterior Poit Algorithms 1 Outlie 1 Barrier Methods Slide 1 The Cetral Path 3 Aroximatig the Cetral Path 4 The Primal Barrier Algorithm 5 The Primal-Dual Barrier

More information

HWA CHONG INSTITUTION JC1 PROMOTIONAL EXAMINATION Wednesday 1 October hours. List of Formula (MF15)

HWA CHONG INSTITUTION JC1 PROMOTIONAL EXAMINATION Wednesday 1 October hours. List of Formula (MF15) HWA CHONG INSTITUTION JC PROMOTIONAL EXAMINATION 4 MATHEMATICS Higher 974/ Paper Wedesda October 4 hors Additioal materials: Aswer paper List of Formla (MF5) READ THESE INSTRUCTIONS FIRST Write or ame

More information

PAIR OF STRAIGHT LINES.

PAIR OF STRAIGHT LINES. PAIR OF STRAIGHT LINES PREVIOUS EAMCET BITS 1. The value of λ with λ < 16 suh that x 1xy + 1y + 5x + λy 3 = represets a pair of straight lies, is [EAMCET 9] 1) 1 ) 9 3) 1 4)9 As: Sol. Δ= λ= 9. The area

More information

Representing transformations by matrices

Representing transformations by matrices Teachig Further Mathematics FP Give each pair of studets a copy of the sheet below elarged oto A. Represetig trasformatios by matrices Studets have to multiply the matri by the positio vector of each verte

More information

Z-buffering, Interpolation and More W-buffering Doug Rogers NVIDIA Corporation

Z-buffering, Interpolation and More W-buffering Doug Rogers NVIDIA Corporation -buerig, Iterpolatio a More -buerig Doug Roger NVIDIA Corporatio roger@viia.om Itroutio Covertig ooriate rom moel pae to ree pae i a erie o operatio that mut be learly uertoo a implemete or viibility problem

More information

Chapter 2. Finite Fields (Chapter 3 in the text)

Chapter 2. Finite Fields (Chapter 3 in the text) Chater 2. Fiite Fields (Chater 3 i the tet 1. Grou Structures 2. Costructios of Fiite Fields GF(2 ad GF( 3. Basic Theory of Fiite Fields 4. The Miimal Polyomials 5. Trace Fuctios 6. Subfields 1. Grou Structures

More information

Lecture 7: Linear Classification Methods

Lecture 7: Linear Classification Methods Homeork Homeork Lecture 7: Liear lassificatio Methods Fial rojects? Grous Toics Proosal eek 5 Lecture is oster sessio, Jacobs Hall Lobb, sacks Fial reort 5 Jue. What is liear classificatio? lassificatio

More information

FAILURE CRITERIA: MOHR S CIRCLE AND PRINCIPAL STRESSES

FAILURE CRITERIA: MOHR S CIRCLE AND PRINCIPAL STRESSES LECTURE Third Editio FAILURE CRITERIA: MOHR S CIRCLE AND PRINCIPAL STRESSES A. J. Clark School of Egieerig Departmet of Civil ad Evirometal Egieerig Chapter 7.4 b Dr. Ibrahim A. Assakkaf SPRING 3 ENES

More information

Computational Methods CMSC/AMSC/MAPL 460. Quadrature: Integration

Computational Methods CMSC/AMSC/MAPL 460. Quadrature: Integration Computatioal Metods CMSC/AMSC/MAPL 6 Quadrature: Itegratio Ramai Duraiswami, Dept. o Computer Siee Some material adapted rom te olie slides o Eri Sadt ad Diae O Leary Numerial Itegratio Idea is to do itegral

More information

CS420/ S-04 Intro to 3D Math 1

CS420/ S-04 Intro to 3D Math 1 CS420/686-2016S-04 Intro to 3D Math 1 04-0: Right-Handed vs. Left-Handed Hold out our left hand (reall, do it!): Thum to the right Inde finder up Middle finger straight ahead This forms a asis for a 3D

More information

Dipartimento di Elettronica e Informazione e Bioingegneria Robotics

Dipartimento di Elettronica e Informazione e Bioingegneria Robotics Diartimeto di Elettroica e Iformaioe e Bioigegeria Robotics arm iverse kiematics @ 5 IK ad robot rogrammig amera Tool gras referece sstem o the object the had has to reach the gras referece: T gras IK

More information

University of Washington Department of Chemistry Chemistry 453 Winter Quarter 2015

University of Washington Department of Chemistry Chemistry 453 Winter Quarter 2015 Uiversity of Wasigto Departmet of Cemistry Cemistry 453 Witer Quarter 15 Lecture 14. /11/15 Recommeded Text Readig: Atkis DePaula: 9.1, 9., 9.3 A. Te Equipartitio Priciple & Eergy Quatizatio Te Equipartio

More information

NBHM QUESTION 2007 Section 1 : Algebra Q1. Let G be a group of order n. Which of the following conditions imply that G is abelian?

NBHM QUESTION 2007 Section 1 : Algebra Q1. Let G be a group of order n. Which of the following conditions imply that G is abelian? NBHM QUESTION 7 NBHM QUESTION 7 NBHM QUESTION 7 Sectio : Algebra Q Let G be a group of order Which of the followig coditios imply that G is abelia? 5 36 Q Which of the followig subgroups are ecesarily

More information

When dealing with series, n is always a positive integer. Remember at every, sine has a value of zero, which means

When dealing with series, n is always a positive integer. Remember at every, sine has a value of zero, which means Fourier Series Some Prelimiar Ideas: Odd/Eve Fuctios: Sie is odd, which meas si ( ) si Cosie is eve, which meas cos ( ) cos Secial values of siie a cosie at Whe dealig with series, is alwas a ositive iteger.

More information

(8) 1f = f. can be viewed as a real vector space where addition is defined by ( a1+ bi

(8) 1f = f. can be viewed as a real vector space where addition is defined by ( a1+ bi Geeral Liear Spaes (Vetor Spaes) ad Solutios o ODEs Deiitio: A vetor spae V is a set, with additio ad salig o elemet deied or all elemets o the set, that is losed uder additio ad salig, otais a zero elemet

More information

Vector Spaces and Vector Subspaces. Remarks. Euclidean Space

Vector Spaces and Vector Subspaces. Remarks. Euclidean Space Vector Spaces ad Vector Subspaces Remarks Let be a iteger. A -dimesioal vector is a colum of umbers eclosed i brackets. The umbers are called the compoets of the vector. u u u u Euclidea Space I Euclidea

More information

Balancing. Rotating Components Examples of rotating components in a mechanism or a machine. (a)

Balancing. Rotating Components Examples of rotating components in a mechanism or a machine. (a) alacig NOT COMPLETE Rotatig Compoets Examples of rotatig compoets i a mechaism or a machie. Figure 1: Examples of rotatig compoets: camshaft; crakshaft Sigle-Plae (Static) alace Cosider a rotatig shaft

More information

(VII.A) Review of Orthogonality

(VII.A) Review of Orthogonality VII.A Review of Orthogoality At the begiig of our study of liear trasformatios i we briefly discussed projectios, rotatios ad projectios. I III.A, projectios were treated i the abstract ad without regard

More information

( ) ( ) ( ) notation: [ ]

( ) ( ) ( ) notation: [ ] Liear Algebra Vectors ad Matrices Fudametal Operatios with Vectors Vector: a directed lie segmets that has both magitude ad directio =,,,..., =,,,..., = where 1, 2,, are the otatio: [ ] 1 2 3 1 2 3 compoets

More information

Systems of Particles: Angular Momentum and Work Energy Principle

Systems of Particles: Angular Momentum and Work Energy Principle 1 2.003J/1.053J Dyamics ad Cotrol I, Sprig 2007 Professor Thomas Peacock 2/20/2007 Lecture 4 Systems of Particles: Agular Mometum ad Work Eergy Priciple Systems of Particles Agular Mometum (cotiued) τ

More information

Introduction. Question: Why do we need new forms of parametric curves? Answer: Those parametric curves discussed are not very geometric.

Introduction. Question: Why do we need new forms of parametric curves? Answer: Those parametric curves discussed are not very geometric. Itrodctio Qestio: Why do we eed ew forms of parametric crves? Aswer: Those parametric crves discssed are ot very geometric. Itrodctio Give sch a parametric form, it is difficlt to kow the derlyig geometry

More information

MATHEMATICS: PAPER II Page 1 of 11 HILTON COLLEGE TRIAL EXAMINATION AUGUST 2013 MATHEMATICS: PAPER II GENERAL INSTRUCTIONS

MATHEMATICS: PAPER II Page 1 of 11 HILTON COLLEGE TRIAL EXAMINATION AUGUST 2013 MATHEMATICS: PAPER II GENERAL INSTRUCTIONS MATHEMATICS: PAPER II Page 1 of 11 HILTON COLLEGE TRIAL EXAMINATION AUGUST 013 Time: 3 hours MATHEMATICS: PAPER II GENERAL INSTRUCTIONS 150 marks PLEASE READ THE FOLLOWING INSTRUCTIONS CAREFULLY. 1. This

More information

CHAPTER 6c. NUMERICAL INTERPOLATION

CHAPTER 6c. NUMERICAL INTERPOLATION CHAPTER 6c. NUMERICAL INTERPOLATION A. J. Clark School o Egieerig Departmet o Civil ad Evirometal Egieerig y Dr. Irahim A. Assakka Sprig ENCE - Computatio Methods i Civil Egieerig II Departmet o Civil

More information

A widely used display of protein shapes is based on the coordinates of the alpha carbons - - C α

A widely used display of protein shapes is based on the coordinates of the alpha carbons - - C α Nice plottig of proteis: I A widely used display of protei shapes is based o the coordiates of the alpha carbos - - C α -s. The coordiates of the C α -s are coected by a cotiuous curve that roughly follows

More information

M 340L CS Homew ork Set 6 Solutions

M 340L CS Homew ork Set 6 Solutions 1. Suppose P is ivertible ad M 34L CS Homew ork Set 6 Solutios A PBP 1. Solve for B i terms of P ad A. Sice A PBP 1, w e have 1 1 1 B P PBP P P AP ( ).. Suppose ( B C) D, w here B ad C are m matrices ad

More information

M 340L CS Homew ork Set 6 Solutions

M 340L CS Homew ork Set 6 Solutions . Suppose P is ivertible ad M 4L CS Homew ork Set 6 Solutios A PBP. Solve for B i terms of P ad A. Sice A PBP, w e have B P PBP P P AP ( ).. Suppose ( B C) D, w here B ad C are m matrices ad D is ivertible.

More information

Lecture 6. Material from Various Sources, Mainly Nise Chapters 5.8 and 12. Similarity Transformations and Introduction to State-Space Control

Lecture 6. Material from Various Sources, Mainly Nise Chapters 5.8 and 12. Similarity Transformations and Introduction to State-Space Control ETR Advaced Cotrol Lectre 6 aterial from Vario Sorce, ail Nie Chater.8 ad ETR ADVANCED CONTROL SEESTER, Similarit Traformatio ad Itrodctio to State-Sace Cotrol G. Hovlad Z. Dog State-Sace Deig v Freqec

More information

Principal Component Analysis

Principal Component Analysis Priipal Compoet Aalysis Nuo Vasoelos (Ke Kreutz-Delgado) UCSD Curse of dimesioality Typial observatio i Bayes deisio theory: Error ireases whe umber of features is large Eve for simple models (e.g. Gaussia)

More information

Lecture 8: October 20, Applications of SVD: least squares approximation

Lecture 8: October 20, Applications of SVD: least squares approximation Mathematical Toolkit Autum 2016 Lecturer: Madhur Tulsiai Lecture 8: October 20, 2016 1 Applicatios of SVD: least squares approximatio We discuss aother applicatio of sigular value decompositio (SVD) of

More information

U8L1: Sec Equations of Lines in R 2

U8L1: Sec Equations of Lines in R 2 MCVU U8L: Sec. 8.9. Equatios of Lies i R Review of Equatios of a Straight Lie (-D) Cosider the lie passig through A (-,) with slope, as show i the diagram below. I poit slope form, the equatio of the lie

More information

Section 10.3 The Complex Plane; De Moivre's Theorem. abi

Section 10.3 The Complex Plane; De Moivre's Theorem. abi Sectio 03 The Complex Plae; De Moivre's Theorem REVIEW OF COMPLEX NUMBERS FROM COLLEGE ALGEBRA You leared about complex umbers of the form a + bi i your college algebra class You should remember that "i"

More information

(c) Write, but do not evaluate, an integral expression for the volume of the solid generated when R is

(c) Write, but do not evaluate, an integral expression for the volume of the solid generated when R is Calculus BC Fial Review Name: Revised 7 EXAM Date: Tuesday, May 9 Remiders:. Put ew batteries i your calculator. Make sure your calculator is i RADIAN mode.. Get a good ight s sleep. Eat breakfast. Brig:

More information

CS537. Numerical Analysis and Computing

CS537. Numerical Analysis and Computing CS57 Numerical Aalysis ad Computig Lecture Locatig Roots o Equatios Proessor Ju Zhag Departmet o Computer Sciece Uiversity o Ketucky Leigto KY 456-6 Jauary 9 9 What is the Root May physical system ca be

More information

Circular Functions (Trigonometry)

Circular Functions (Trigonometry) Circular Fuctios (Trigoometry) Circular fuctios Revisio Where do si cos ad ta come from? Uit circle (of radius ) cos is the coordiate si is the y coordiate si ta cos all are measures of legth. Remember

More information

4/9/13. Fibonacci Heaps. H.min. H.min. Priority Queues Performance Cost Summary. COMP 160 Algorithms - Tufts University

4/9/13. Fibonacci Heaps. H.min. H.min. Priority Queues Performance Cost Summary. COMP 160 Algorithms - Tufts University 4/9/ Priority Queues Performace Cost Summary Fiboacci Heas Oeratio Liked List Biary Hea Biomial Hea Fiboacci Hea Relaed Hea make-hea COMP 60 Algorithms - Tufts Uiversity is-emty isert Origial Slides from

More information

Chapter 7. Support Vector Machine

Chapter 7. Support Vector Machine Chapter 7 Support Vector Machie able of Cotet Margi ad support vectors SVM formulatio Slack variables ad hige loss SVM for multiple class SVM ith Kerels Relevace Vector Machie Support Vector Machie (SVM)

More information

Chapter 2: Rigid Body Motions and Homogeneous Transforms

Chapter 2: Rigid Body Motions and Homogeneous Transforms Chater : igi Bo Motion an Homogeneou Tranform (original lie b Stee from Harar) ereenting oition Definition: oorinate frame Aetn n of orthonormal bai etor anning n For eamle When rereenting a oint we nee

More information

A Study of H -Function of Two Variables

A Study of H -Function of Two Variables ISSN: 19-875 (A ISO 97: 007 Certified Orgaizatio) Vol., Issue 9, Setember 01 A Study of -Fuctio of Two Variables Yashwat Sigh 1 armedra Kumar Madia Lecturer, Deartmet of Mathematics, Goermet College, Kaladera,

More information

Pascal Pyramids, Pascal Hyper-Pyramids and a Bilateral Multinomial Theorem

Pascal Pyramids, Pascal Hyper-Pyramids and a Bilateral Multinomial Theorem Pascal Pramids, Pascal Hper-Pramids ad a Bilateral Multiomial Theorem Marti Eri Hor, Uiversit o Potsdam Am Neue Palais, D - 69 Potsdam, Germa E-Mail: marhor@rz.ui-potsdam.de Abstract Part I: The two-dimesioal

More information

Round-off Errors and Computer Arithmetic - (1.2)

Round-off Errors and Computer Arithmetic - (1.2) Roud-off Errors ad Comuter Arithmetic - (1.) 1. Roud-off Errors: Roud-off errors is roduced whe a calculator or comuter is used to erform real umber calculatios. That is because the arithmetic erformed

More information

Lesson 8 Refraction of Light

Lesson 8 Refraction of Light Physis 30 Lesso 8 Refratio of Light Refer to Pearso pages 666 to 674. I. Refletio ad Refratio of Light At ay iterfae betwee two differet mediums, some light will be refleted ad some will be refrated, exept

More information

The Stokes Theorem. (Sect. 16.7) The curl of a vector field in space

The Stokes Theorem. (Sect. 16.7) The curl of a vector field in space The tokes Theorem. (ect. 6.7) The curl of a vector field i space. The curl of coservative fields. tokes Theorem i space. Idea of the proof of tokes Theorem. The curl of a vector field i space Defiitio

More information

Ma 4121: Introduction to Lebesgue Integration Solutions to Homework Assignment 5

Ma 4121: Introduction to Lebesgue Integration Solutions to Homework Assignment 5 Ma 42: Itroductio to Lebesgue Itegratio Solutios to Homework Assigmet 5 Prof. Wickerhauser Due Thursday, April th, 23 Please retur your solutios to the istructor by the ed of class o the due date. You

More information

School of Mechanical Engineering Purdue University. ME375 Transfer Functions - 1

School of Mechanical Engineering Purdue University. ME375 Transfer Functions - 1 Trasfer Fuctio Aalysis Free & Forced Resposes Trasfer Fuctio Syste Stability ME375 Trasfer Fuctios - 1 Free & Forced Resposes Ex: Let s look at a stable first order syste: y y Ku Take LT of the I/O odel

More information

Problem 1. Problem Engineering Dynamics Problem Set 9--Solution. Find the equation of motion for the system shown with respect to:

Problem 1. Problem Engineering Dynamics Problem Set 9--Solution. Find the equation of motion for the system shown with respect to: 2.003 Egieerig Dyamics Problem Set 9--Solutio Problem 1 Fid the equatio of motio for the system show with respect to: a) Zero sprig force positio. Draw the appropriate free body diagram. b) Static equilibrium

More information

Course Outline. Course Outline. Computer Graphics (Fall 2008) Motivation. Outline of Unit. Bezier Curve (with HW2 demo)

Course Outline. Course Outline. Computer Graphics (Fall 2008) Motivation. Outline of Unit. Bezier Curve (with HW2 demo) Compter Graphics (Fall 2008) COMS 4160, Lectre 6: Crves 1 http://www.cs.colmbia.ed/~cs4160 3D Graphics Pipelie Modelig (Creatig 3D Geometry) Corse Otlie Rederig (Creatig, shadig images from geometry, lightig,

More information

Miscellaneous (dimension, angle, etc.) - black [pencil] Use different colors in diagrams. Body outline - blue [black] Vector

Miscellaneous (dimension, angle, etc.) - black [pencil] Use different colors in diagrams. Body outline - blue [black] Vector 1. Sstems of orces & s 2142111 Statics, 2011/2 Department of Mechanical Engineering, Chulalongkorn Uniersit bjecties Students must be able to Course bjectie Analze a sstem of forces and moments Chapter

More information

Notes The Incremental Motion Model:

Notes The Incremental Motion Model: The Icremetal Motio Model: The Jacobia Matrix I the forward kiematics model, we saw that it was possible to relate joit agles θ, to the cofiguratio of the robot ed effector T I this sectio, we will see

More information

CHAPTER 6d. NUMERICAL INTERPOLATION

CHAPTER 6d. NUMERICAL INTERPOLATION CHAPER 6d. NUMERICAL INERPOLAION A. J. Clark School o Egieerig Departmet o Civil ad Evirometal Egieerig by Dr. Ibrahim A. Assakka Sprig ENCE - Computatio Methods i Civil Egieerig II Departmet o Civil ad

More information

Unit 5. Hypersurfaces

Unit 5. Hypersurfaces Uit 5. Hyersurfaces ================================================================= -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

More information

Machine Learning for Data Science (CS 4786)

Machine Learning for Data Science (CS 4786) Machie Learig for Data Sciece CS 4786) Lecture 9: Pricipal Compoet Aalysis The text i black outlies mai ideas to retai from the lecture. The text i blue give a deeper uderstadig of how we derive or get

More information

Fractal geometry extends classical geometry and is more fun too!

Fractal geometry extends classical geometry and is more fun too! Fractal Geometr Reasos for studig this geometr : Fractal geometr eteds classical geometr ad is more fu too! (i) (ii) etesio of classical geometr such as Euclidea geometr, projective geometr I classical

More information

Chapter 5: Take Home Test

Chapter 5: Take Home Test Chapter : Take Home Test AB Calulus - Hardtke Name Date: Tuesday, / MAY USE YOUR CALCULATOR FOR THIS PAGE. Roud aswers to three plaes. Sore: / Show diagrams ad work to justify eah aswer.. Approimate the

More information

Cov(aX, cy ) Var(X) Var(Y ) It is completely invariant to affine transformations: for any a, b, c, d R, ρ(ax + b, cy + d) = a.s. X i. as n.

Cov(aX, cy ) Var(X) Var(Y ) It is completely invariant to affine transformations: for any a, b, c, d R, ρ(ax + b, cy + d) = a.s. X i. as n. CS 189 Itroductio to Machie Learig Sprig 218 Note 11 1 Caoical Correlatio Aalysis The Pearso Correlatio Coefficiet ρ(x, Y ) is a way to measure how liearly related (i other words, how well a liear model

More information

Algebra of Least Squares

Algebra of Least Squares October 19, 2018 Algebra of Least Squares Geometry of Least Squares Recall that out data is like a table [Y X] where Y collects observatios o the depedet variable Y ad X collects observatios o the k-dimesioal

More information

International ejournals

International ejournals Available olie at www.iteratioalejourals.com ISSN 976 4 Iteratioal ejourals Iteratioal ejoural o Mathematics ad Egieerig 95 () 864-874 A MATHEMATICAL MODEL OF FLUID FLOW BETWEEN POROUS PARALLEL OSILATING

More information

Lecture Notes Trigonometric Limits page 1

Lecture Notes Trigonometric Limits page 1 Lecture Notes Trigoometric Limits age Theorem : si! Proof: This theorem ad the et oe are ecessary for di eretiatig si ad cos. Recall a theorem: Let r be the radius of a circle. If is measured i radias,

More information

Rigid Body Transforms-3D. J.C. Dill transforms3d 27Jan99

Rigid Body Transforms-3D. J.C. Dill transforms3d 27Jan99 ESC 489 3D ransforms 1 igid Bod ransforms-3d J.C. Dill transforms3d 27Jan99 hese notes on (2D and) 3D rigid bod transform are currentl in hand-done notes which are being converted to this file from that

More information

CS 332: Algorithms. Linear-Time Sorting. Order statistics. Slide credit: David Luebke (Virginia)

CS 332: Algorithms. Linear-Time Sorting. Order statistics. Slide credit: David Luebke (Virginia) 1 CS 332: Algorithms Liear-Time Sortig. Order statistics. Slide credit: David Luebke (Virgiia) Quicksort: Partitio I Words Partitio(A, p, r): Select a elemet to act as the pivot (which?) Grow two regios,

More information

Dividing Algebraic Fractions

Dividing Algebraic Fractions Leig Eheme Tem Model Awe: Mlilig d Diidig Algei Fio Mlilig d Diidig Algei Fio d gide ) Yo e he me mehod o mlil lgei io o wold o mlil meil io. To id he meo o he we o mlil he meo o he io i he eio. Simill

More information

A brief introduction to linear algebra

A brief introduction to linear algebra CHAPTER 6 A brief itroductio to liear algebra 1. Vector spaces ad liear maps I what follows, fix K 2{Q, R, C}. More geerally, K ca be ay field. 1.1. Vector spaces. Motivated by our ituitio of addig ad

More information

PAPER : IIT-JAM 2010

PAPER : IIT-JAM 2010 MATHEMATICS-MA (CODE A) Q.-Q.5: Oly oe optio is correct for each questio. Each questio carries (+6) marks for correct aswer ad ( ) marks for icorrect aswer.. Which of the followig coditios does NOT esure

More information

Grouping 2: Spectral and Agglomerative Clustering. CS 510 Lecture #16 April 2 nd, 2014

Grouping 2: Spectral and Agglomerative Clustering. CS 510 Lecture #16 April 2 nd, 2014 Groupig 2: Spectral ad Agglomerative Clusterig CS 510 Lecture #16 April 2 d, 2014 Groupig (review) Goal: Detect local image features (SIFT) Describe image patches aroud features SIFT, SURF, HoG, LBP, Group

More information

Elliptic Curves Spring 2017 Problem Set #1

Elliptic Curves Spring 2017 Problem Set #1 18.783 Ellitic Curves Srig 017 Problem Set #1 These roblems are related to the material covered i Lectures 1-3. Some of them require the use of Sage; you will eed to create a accout at the SageMathCloud.

More information

U8L1: Sec Equations of Lines in R 2

U8L1: Sec Equations of Lines in R 2 MCVU Thursda Ma, Review of Equatios of a Straight Lie (-D) U8L Sec. 8.9. Equatios of Lies i R Cosider the lie passig through A (-,) with slope, as show i the diagram below. I poit slope form, the equatio

More information

THE MEASUREMENT OF THE SPEED OF THE LIGHT

THE MEASUREMENT OF THE SPEED OF THE LIGHT THE MEASUREMENT OF THE SPEED OF THE LIGHT Nyamjav, Dorjderem Abstrat The oe of the physis fudametal issues is a ature of the light. I this experimet we measured the speed of the light usig MihelsoÕs lassial

More information

Number Of Real Zeros Of Random Trigonometric Polynomial

Number Of Real Zeros Of Random Trigonometric Polynomial Iteratioal Joral of Comtatioal iee ad Mathematis. IN 97-389 Volme 7, Nmer (5),. 9- Iteratioal Researh Pliatio Hose htt://www.irhose.om Nmer Of Real Zeros Of Radom Trigoometri Polyomial Dr.P.K.Mishra, DR.A.K.Mahaatra,

More information

Math 21C Brian Osserman Practice Exam 2

Math 21C Brian Osserman Practice Exam 2 Math 1C Bria Osserma Practice Exam 1 (15 pts.) Determie the radius ad iterval of covergece of the power series (x ) +1. First we use the root test to determie for which values of x the series coverges

More information

Propagation of error for multivariable function

Propagation of error for multivariable function Proagation o error or mltiariable nction No consider a mltiariable nction (,,, ). I measrements o,,,. All hae ncertaint,,,., ho ill this aect the ncertaint o the nction? L tet) o (Eqation (3.8) ± L ),...,,

More information

CALCULATING FIBONACCI VECTORS

CALCULATING FIBONACCI VECTORS THE GENERALIZED BINET FORMULA FOR CALCULATING FIBONACCI VECTORS Stuart D Aderso Departmet of Physics, Ithaca College 953 Daby Road, Ithaca NY 14850, USA email: saderso@ithacaedu ad Dai Novak Departmet

More information

Least Squares Methods

Least Squares Methods Det. of Biomed. Eg. BME80: Iverse Problems i Bioegieerig Kug ee Uiv. Least Squares Methods Overdetermied liear equatios m where R ad m > More equatios tha ukows Caot solve for i most cases. Least squares

More information

Analytical mechanics

Analytical mechanics Divisio of Mechaics Lud Uiversity Aalytical mechaics 7059 Name (write i block letters):. Id.-umber: Writte examiatio with five tasks. Please check that all tasks are icluded. A clea copy of the solutios

More information

After the completion of this section the student. V.4.2. Power Series Solution. V.4.3. The Method of Frobenius. V.4.4. Taylor Series Solution

After the completion of this section the student. V.4.2. Power Series Solution. V.4.3. The Method of Frobenius. V.4.4. Taylor Series Solution Chapter V ODE V.4 Power Series Solutio Otober, 8 385 V.4 Power Series Solutio Objetives: After the ompletio of this setio the studet - should reall the power series solutio of a liear ODE with variable

More information

( ) ( ) ( ) ( ) TNM046: Datorgrafik. Transformations. Linear Algebra. Linear Algebra. Sasan Gooran VT Transposition. Scalar (dot) product:

( ) ( ) ( ) ( ) TNM046: Datorgrafik. Transformations. Linear Algebra. Linear Algebra. Sasan Gooran VT Transposition. Scalar (dot) product: TNM046: Datorgrafik Transformations Sasan Gooran VT 04 Linear Algebra ( ) ( ) =,, 3 =,, 3 Transposition t = 3 t = 3 Scalar (dot) product: Length (Norm): = t = + + 3 3 = = + + 3 Normaliation: ˆ = Linear

More information

Most text will write ordinary derivatives using either Leibniz notation 2 3. y + 5y= e and y y. xx tt t

Most text will write ordinary derivatives using either Leibniz notation 2 3. y + 5y= e and y y. xx tt t Itroductio to Differetial Equatios Defiitios ad Termiolog Differetial Equatio: A equatio cotaiig the derivatives of oe or more depedet variables, with respect to oe or more idepedet variables, is said

More information

UNIVERSITY OF NORTHERN COLORADO MATHEMATICS CONTEST. First Round For all Colorado Students Grades 7-12 November 3, 2007

UNIVERSITY OF NORTHERN COLORADO MATHEMATICS CONTEST. First Round For all Colorado Students Grades 7-12 November 3, 2007 UNIVERSITY OF NORTHERN COLORADO MATHEMATICS CONTEST First Roud For all Colorado Studets Grades 7- November, 7 The positive itegers are,,, 4, 5, 6, 7, 8, 9,,,,. The Pythagorea Theorem says that a + b =

More information

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities Polyomials with Ratioal Roots that Differ by a No-zero Costat Philip Gibbs The problem of fidig two polyomials P(x) ad Q(x) of a give degree i a sigle variable x that have all ratioal roots ad differ by

More information

Calculus. Ramanasri. Previous year Questions from 2016 to

Calculus. Ramanasri. Previous year Questions from 2016 to ++++++++++ Calculus Previous ear Questios from 6 to 99 Ramaasri 7 S H O P NO- 4, S T F L O O R, N E A R R A P I D F L O U R M I L L S, O L D R A J E N D E R N A G A R, N E W D E L H I. W E B S I T E :

More information

CDS 101: Lecture 5.1 Controllability and State Space Feedback

CDS 101: Lecture 5.1 Controllability and State Space Feedback CDS, Lecture 5. CDS : Lecture 5. Cotrollability ad State Space Feedback Richard M. Murray 8 October Goals: Deie cotrollability o a cotrol system Give tests or cotrollability o liear systems ad apply to

More information