Handout #2. Introduction to Matrix: Matrix operations & Geometric meaning

Similar documents
Statistics for Financial Engineering Session 1: Linear Algebra Review March 18 th, 2006

Lesson 4 Linear Algebra

The total number of permutations of S is n!. We denote the set of all permutations of S by

Chapter System of Equations

Section 7.3, Systems of Linear Algebraic Equations; Linear Independence, Eigenvalues, Eigenvectors (the variable vector of the system) and

Lecture 2: Matrix Algebra

ECE 102 Engineering Computation

Elementary Linear Algebra

Notes 17 Sturm-Liouville Theory

Vectors. Vectors in Plane ( 2

M.A. (ECONOMICS) PART-I PAPER - III BASIC QUANTITATIVE METHODS

Basic Maths. Fiorella Sgallari University of Bologna, Italy Faculty of Engineering Department of Mathematics - CIRAM

Inner Product Spaces (Chapter 5)

For all Engineering Entrance Examinations held across India. Mathematics

Dynamics of Structures

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1.

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k.

Lecture 3: A brief background to multivariate statistics

Matrix Algebra Notes

Orthogonality, orthogonalization, least squares

DETERMINANT. = 0. The expression a 1. is called a determinant of the second order, and is denoted by : y + c 1

Week 13 Notes: 1) Riemann Sum. Aim: Compute Area Under a Graph. Suppose we want to find out the area of a graph, like the one on the right:

Project 3: Using Identities to Rewrite Expressions

FREE Download Study Package from website: &

Canonical Form and Separability of PPT States on Multiple Quantum Spaces

A GENERALIZATION OF GAUSS THEOREM ON QUADRATIC FORMS

RULES FOR MANIPULATING SURDS b. This is the addition law of surds with the same radicals. (ii)

We will begin by supplying the proof to (a).

Fig. 1. I a. V ag I c. I n. V cg. Z n Z Y. I b. V bg

Physics of Semiconductor Devices Vol.10

Presentation for use with the textbook, Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, Divide-and-Conquer

Mathematical Notations and Symbols xi. Contents: 1. Symbols. 2. Functions. 3. Set Notations. 4. Vectors and Matrices. 5. Constants and Numbers

BRILLIANT PUBLIC SCHOOL, SITAMARHI (Affiliated up to +2 level to C.B.S.E., New Delhi)

Lecture 38 (Trapped Particles) Physics Spring 2018 Douglas Fields

Limit of a function:

lecture 16: Introduction to Least Squares Approximation

Westchester Community College Elementary Algebra Study Guide for the ACCUPLACER

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

Chapter Real Numbers

Solving Systems of Equations

Lecture 4 Recursive Algorithm Analysis. Merge Sort Solving Recurrences The Master Theorem

Assessment Center Elementary Algebra Study Guide for the ACCUPLACER (CPT)

Chapter 2 Infinite Series Page 1 of 9

Chapter 7 Infinite Series

Schrödinger Equation Via Laplace-Beltrami Operator

Remarks: (a) The Dirac delta is the function zero on the domain R {0}.

Section IV.6: The Master Method and Applications

Sect Simplifying Radical Expressions. We can use our properties of exponents to establish two properties of radicals: and

General properties of definite integrals

7 The Rudiments of Input-Output Mathematics

SUTCLIFFE S NOTES: CALCULUS 2 SWOKOWSKI S CHAPTER 11

PROBLEM SET I (Suggested Solutions)

Linear Algebra. Lecture 1 September 19, 2011

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2

Summer MA Lesson 4 Section P.3. such that =, denoted by =, is the principal square root

Addendum. Addendum. Vector Review. Department of Computer Science and Engineering 1-1

Autar Kaw Benjamin Rigsby. Transforming Numerical Methods Education for STEM Undergraduates

Name of the Student:

Chapter Real Numbers

The Elementary Arithmetic Operators of Continued Fraction

Max-norm and Square-max Norm of Fuzzy Matrices

Unit 1. Extending the Number System. 2 Jordan School District

SOLUTION OF SYSTEM OF LINEAR EQUATIONS. Lecture 4: (a) Jacobi's method. method (general). (b) Gauss Seidel method.

Mathacle. PSet Stats, Concepts In Statistics Level Number Name: Date:

INFINITE SERIES. ,... having infinite number of terms is called infinite sequence and its indicated sum, i.e., a 1

MATRIX ALGEBRA, Systems Linear Equations

M3P14 EXAMPLE SHEET 1 SOLUTIONS

MTH 146 Class 16 Notes

Fast Fourier Transform 1) Legendre s Interpolation 2) Vandermonde Matrix 3) Roots of Unity 4) Polynomial Evaluation

Linford 1. Kyle Linford. Math 211. Honors Project. Theorems to Analyze: Theorem 2.4 The Limit of a Function Involving a Radical (A4)

Linear Programming. Preliminaries

ICS141: Discrete Mathematics for Computer Science I

Inverse Matrix. A meaning that matrix B is an inverse of matrix A.

CHAPTER 2d. MATRICES

Convergence rates of approximate sums of Riemann integrals

ALGEBRA. Set of Equations. have no solution 1 b1. Dependent system has infinitely many solutions

Particle in a Box. and the state function is. In this case, the Hermitian operator. The b.c. restrict us to 0 x a. x A sin for 0 x a, and 0 otherwise

Chapter 3 MATRIX. In this chapter: 3.1 MATRIX NOTATION AND TERMINOLOGY

2.Decision Theory of Dependence

Numerical Methods (CENG 2002) CHAPTER -III LINEAR ALGEBRAIC EQUATIONS. In this chapter, we will deal with the case of determining the values of x 1

Numerical Solution of Fuzzy Fredholm Integral Equations of the Second Kind using Bernstein Polynomials

Chapters 4-5 Linear Models & Matrix Algebra

Module 4. Signal Representation and Baseband Processing. Version 2 ECE IIT, Kharagpur

Geometric Sequences. Geometric Sequence. Geometric sequences have a common ratio.

Chapter 11 Design of State Variable Feedback Systems

ALGEBRA II CHAPTER 7 NOTES. Name

Intermediate Applications of Vectors and Matrices Ed Stanek

B. Examples 1. Finite Sums finite sums are an example of Riemann Sums in which each subinterval has the same length and the same x i

Crushed Notes on MATH132: Calculus

Advanced Algorithmic Problem Solving Le 6 Math and Search

UNIT 4 EXTENDING THE NUMBER SYSTEM Lesson 1: Working with the Number System Instruction

[ 20 ] 1. Inequality exists only between two real numbers (not complex numbers). 2. If a be any real number then one and only one of there hold.

A GENERAL METHOD FOR SOLVING ORDINARY DIFFERENTIAL EQUATIONS: THE FROBENIUS (OR SERIES) METHOD

In an algebraic expression of the form (1), like terms are terms with the same power of the variables (in this case

ENGR 3861 Digital Logic Boolean Algebra. Fall 2007

Similar idea to multiplication in N, C. Divide and conquer approach provides unexpected improvements. Naïve matrix multiplication

Approximate Integration

MATH 118 HW 7 KELLY DOUGAN, ANDREW KOMAR, MARIA SIMBIRSKY, BRANDEN LASKE

The Reimann Integral is a formal limit definition of a definite integral

Fundamentals of Mathematics. Pascal s Triangle An Investigation March 20, 2008 Mario Soster

Transcription:

Hdout # Title: FAE Course: Eco 8/ Sprig/5 Istructor: Dr I-Mig Chiu Itroductio to Mtrix: Mtrix opertios & Geometric meig Mtrix: rectgulr rry of umers eclosed i pretheses or squre rckets It is covetiolly deoted y cpitl letter Mtrix is powerful tool to orgize dt A lot of sttisticl methods ivolve the mipultio ie, trsformtio of dt mtrix, the elemet i mtrix A is deoted y i, ; the suscript i i th row d th colum re idices tht tell the loctio of elemet i, The lrgest umer of i d tells the dimesio order of mtrix For exmple,, = d mtrix A is of order x red s two y two Cosider other mtrix B, where the elemet is deoted y i, Sice the lrgest i = d lrgest =, the mtrix B is of order x B = Q: wht is the elemet of, d,? c =, d =, e = symol x, with rrow, is ofte used i mth clss Mtrix c is of order x, d is of order x d e is of order x Whe there is oly oe row colum i mtrix, it s termed s row colum vector We c show the vector c & d i the X-Y ple for e, three dimesiol spce is eeded d -, Y Suppose c = [c, c,, c ], the legth orm of c is c = c c c O c, X Q: Plese fid d i the left grph

Alger of Mtrices Equlity of mtrices If B, the i, = i, Exmple:, B = Sclr multiplictio k i, k Exmple: k =, k = 9 c Additio d Sutrctio A B = i,, i Exmple: + =, - = d Mtrix multiplictio A m x d B x p must e coformle AB = m m p p p = p m eg = = X Y Z,,,,,, e=,, Vector e i three-dimesiol spce X, Y, Z e =,, d its orm e = =

eg Numer of crs Numer of uses Mody 5 Tuesdy 5 5 Wedesdy 5 5 Price = $/cr, $8/us, fid the reveue R o Mody, Tuesdy, d Wedesdy 5 R = 5 5 = 5 5 8 Additiol exmple q = 5 7, z =, P = 5, w = 8 Q: Plese show the mout of profit i terms of mtrix opertio eg x + x = x x = - Ax =, where x, x =, = x AB BA, uless B, B = We c get the product of AB ut ot BA e Rk of mtrix: mximum umer of idepedet rows or colums f Trspose of mtrix symol: A T or A, B =

A T =, B T = Rules: A = A A B = A B AB = B A g Specil mtrices g: if the umer of rows equls the umer of colums, it is squre mtrix g: A is squre mtrix, d if A, the A is symmetric mtrix eg, Notice: For symmetric mtrix A, i, =, i i g: Digol mtrix ll the off-digol elemets re zero eg, C = g: Idetity mtrix ll the digol elemets re oe d off-digol elemets re zero eg, I = g5: A squre mtrix A is idempotet if A = A = eg,, A, AA still A do ot chge

h The trce of squre mtrix A x trce + + the sum of ll the digol elemets eg, the trce of the previous idempotet mtrix is oe = / + / + / Q: Wht is the trce of x idetity mtrix? i Determit of squre mtrix det A or show geometric meig Y D -, Suppose O C, X det = Suppose A is x mtrix, where, how do we fid det A Cofctor Expsio pproch: Step : choose y colum or row Step : fid the mior determit of su-mtrix of ech elemet Step : fid the cofctor Step : multiply ech elemet y its cofctor d get the sum of these products Step : choose the first row Step : Mior: A = det = det 5

A = det = det Step : Cofctor C i, = - i + A i, C = - + A Step : det i, C i, or i, C i, if expded y colum i eg, = A = det = 5, C = - + A = 5 A = det = -, C = - + A = A = det = -, C = - + A = - det 5 + - + - = Iversio of squre mtrix A - Defiitio: A - I eg,, let A - = A - =, four equtios d four ukows; we eed to solve simulteous equtio system i order to fid ll the elemets i A - How do we fid the iverse of squre mtrix A x if?

Formul: A - = det A d A, where d A is termed doit mtrix C C C d C C C T = C C C Cofctor C i, = - i + A i, C C C C C C C C C eg, det -5, d A - = det A Doule check: d - 5 = 5 5 5 5 AA - = 5 5 5 = 5 Q: fid the iverse of the followig x mtrix B B -? B = Rules: A - AA - = I A - - = A AB - = B - A - A - = A - 5 det A - = det A 7

Solve Simulteous Lier Equtios x + x = x + x = Let x, x =, = x Ax = A - Ax = A - Ix = A - x = A - we solve x usig iversio pproch Erlier exmple: x + x = x x = - x, x =, = x x = 5 5 5 5 = 5 5 eg Supply d demd model Q = P Q = + P P, x =, = Q P x = = A - / / = Q / / = 8

k Eigevlue Prolem Eigevlue is lso clled ltet vlue or chrcteristic root Aq = q A is kow x symmetric mtrix, is ukow sclr d q is ukow x colum vector The solutio of fidig the ukow sclr Eigevlue d the ukow q Eigevector is clled the Eigevlue prolem eg A - Iq = For otrivil solutio q, A - I x mtrix must e sigulr It mes tht det A - I = A - I = det A - I = - - - = solve for d oti = d = - The umer of o-zero eigevlues c e used to fid the rk of the mtrix I this exmple, there re two o-zero eigevlues Therefore, the mtrix A hs full rk ie, rk or it mes there re two lier idepedet rows colums i mtrix A Next we hve to fid the eigevector: Whe = A - Iq = -q + q = q = / q, where q = [q, q ] T Use the ormliztio coditio: q + q = Solve for q d q we c oti: q = q = 5 5 Eigevector q = 5 correspodig to = 5 Whe = - 9

A - Iq = q + q = q = -q, where q = [q, q ] T Use the ormliztio coditio: q + q = Solve for q d q : q =, q = 5 5 Eigevector q = 5 correspodig to = - 5 Property of q d q : q T T q =, q q = Collect q d q i mtrix Q Where Q = [q, q ] Properties of Q: Q T Q = QQ T = I from previous property, Q T = Q - Q is Orthogol mtrix Q T AQ =, where = Property ove is clled Digoliztio c If A is ot symmetric the Q - AQ = Q is o loger Orthogol d trce trce e det i = Coect the ove results d we hve the followig coclusios: If x mtrix A is osigulr det A iff A - exists c rk full rk Note: iff : if d oly if; equivlet ecessry d sufficiet sttemet symol