Chapter 2 … part1 Matrices Linear Algebra S 1. Ch2_2 2.1 Addition, Scalar Multiplication, and Multiplication of Matrices Definition A matrix is a rectangular.

Slides:



Advertisements
Similar presentations
Matrix.
Advertisements

CSNB143 – Discrete Structure
Chapter Matrices Matrix Arithmetic
Applied Informatics Štefan BEREŽNÝ
Matrix Definition: An array of numbers in m rows and n colums is called an mxn matrix A square matrix of order n, is an (nxn) matrix.
Mathematics. Matrices and Determinants-1 Session.
3_3 An Useful Overview of Matrix Algebra
ECIV 301 Programming & Graphics Numerical Methods for Engineers Lecture 12 System of Linear Equations.
MATRICES. Matrices A matrix is a rectangular array of objects (usually numbers) arranged in m horizontal rows and n vertical columns. A matrix with m.
CE 311 K - Introduction to Computer Methods Daene C. McKinney
3.8 Matrices.
Chapter 1: Matrices Definition 1: A matrix is a rectangular array of numbers arranged in horizontal rows and vertical columns. EXAMPLE:
1 Operations with Matrice 2 Properties of Matrix Operations
Properties of Matrix Operations King Saud University.
1.3 Matrices and Matrix Operations.
ECON 1150 Matrix Operations Special Matrices
Systems of Linear Equation and Matrices
Chap. 2 Matrices 2.1 Operations with Matrices
2 2.1 © 2016 Pearson Education, Inc. Matrix Algebra MATRIX OPERATIONS.
1.3 Matrices and Matrix Operations. Definition A matrix is a rectangular array of numbers. The numbers in the array are called the entries in the matrix.
Matrices. A matrix, A, is a rectangular collection of numbers. A matrix with “m” rows and “n” columns is said to have order m x n. Each entry, or element,
Copyright © 2011 Pearson, Inc. 7.2 Matrix Algebra.
1 C ollege A lgebra Systems and Matrices (Chapter5) 1.
Matrices CHAPTER 8.1 ~ 8.8. Ch _2 Contents  8.1 Matrix Algebra 8.1 Matrix Algebra  8.2 Systems of Linear Algebra Equations 8.2 Systems of Linear.
Lecture 7 Matrices CSCI – 1900 Mathematics for Computer Science Fall 2014 Bill Pine.
Chapter 4 – Matrix CSNB 143 Discrete Mathematical Structures.
Company LOGO Chapter 1: Matrix, Determinant, System of linear equations Module 1: Matrix Natural Science Department Example 1: The following rectangular.
Matrices Matrices For grade 1, undergraduate students For grade 1, undergraduate students Made by Department of Math.,Anqing Teachers college.
Co. Chapter 3 Determinants Linear Algebra. Ch03_2 Let A be an n  n matrix and c be a nonzero scalar. (a)If then |B| = …….. (b)If then |B| = …..... (c)If.
Chapter 3 Determinants Linear Algebra. Ch03_2 3.1 Introduction to Determinants Definition The determinant of a 2  2 matrix A is denoted |A| and is given.
Prepared by Deluar Jahan Moloy Lecturer Northern University Bangladesh
Fundamentals of Engineering Analysis
Chapter 6 Systems of Linear Equations and Matrices Sections 6.3 – 6.5.
Meeting 18 Matrix Operations. Matrix If A is an m x n matrix - that is, a matrix with m rows and n columns – then the scalar entry in the i th row and.
Section 1.4 Inverses; Rules of Matrix Arithmetic.
CSCI 171 Presentation 9 Matrix Theory. Matrix – Rectangular array –i th row, j th column, i,j element –Square matrix, diagonal –Diagonal matrix –Equality.
For real numbers a and b,we always have ab = ba, which is called the commutative law for multiplication. For matrices, however, AB and BA need not be equal.
2 2.1 © 2012 Pearson Education, Inc. Matrix Algebra MATRIX OPERATIONS.
Matrices Section 2.6. Section Summary Definition of a Matrix Matrix Arithmetic Transposes and Powers of Arithmetic Zero-One matrices.
Matrices and Determinants
Linear Algebra Chapter 2 Matrices.
Matrices and Matrix Operations. Matrices An m×n matrix A is a rectangular array of mn real numbers arranged in m horizontal rows and n vertical columns.
Introduction to Financial Modeling MGT 4850 Spring 2008 University of Lethbridge.
Section 2.4. Section Summary  Sequences. o Examples: Geometric Progression, Arithmetic Progression  Recurrence Relations o Example: Fibonacci Sequence.
2 - 1 Chapter 2A Matrices 2A.1 Definition, and Operations of Matrices: 1 Sums and Scalar Products; 2 Matrix Multiplication 2A.2 Properties of Matrix Operations;
Matrix Algebra Definitions Operations Matrix algebra is a means of making calculations upon arrays of numbers (or data). Most data sets are matrix-type.
MATRICES. Introduction Matrix algebra has several uses in economics as well as other fields of study. One important application of Matrices is that it.
Matrices. Variety of engineering problems lead to the need to solve systems of linear equations matrixcolumn vectors.
A very brief introduction to Matrix (Section 2.7) Definitions Some properties Basic matrix operations Zero-One (Boolean) matrices.
MATRICES A rectangular arrangement of elements is called matrix. Types of matrices: Null matrix: A matrix whose all elements are zero is called a null.
2.1 Matrix Operations 2. Matrix Algebra. j -th column i -th row Diagonal entries Diagonal matrix : a square matrix whose nondiagonal entries are zero.
Matrices Introduction.
Matrices and Matrix Operations
Properties and Applications of Matrices
MATRICES.
Linear Algebra Lecture 2.
1.4 Inverses; Rules of Matrix Arithmetic
Rules of Matrix Arithmetic
L6 matrix operations.
Section 7.4 Matrix Algebra.
2. Matrix Algebra 2.1 Matrix Operations.
Matrices Introduction.
Matrices and Matrix Operations
MATRICES Operations with Matrices Properties of Matrix Operations
Multiplication of Matrices
Linear Algebra Lecture 11.
Matrix Operations Ms. Olifer.
3.5 Perform Basic Matrix Operations Algebra II.
Matrices - Operations MULTIPLICATION OF MATRICES
Matrices and Determinants
Presentation transcript:

Chapter 2 … part1 Matrices Linear Algebra S 1

Ch2_2 2.1 Addition, Scalar Multiplication, and Multiplication of Matrices Definition A matrix is a rectangular array of numbers. The numbers in the array are called the elements of the matrix. Denoted by: A,B, … capital letter.

Ch2_3 2.1 Addition, Scalar Multiplication, and Multiplication of Matrices a ij : the element of matrix A in row….. and column …… we say it is in the ……………….. The size of a matrix = number of …... × number of ….….. = ……. If n=m the matrix is said to be a …….. matrix with size = …... or …. A matrix that has one row is called a …… matrix. A matrix that has one column is called a ……….. matrix. For a square n  n matrix A, the main diagonal is: ………………. We can denote the matrix by …………….. Note:

Ch2_4 Definition Two matrices are equal if: 1) ………………….. 2) …………………….. Example 1

Ch2_5 Addition of Matrices Definition If A and B be matrices of the …………….. then the sum A + B=C will be of the ……….. size and …………………… If Let A be a matrix and k be a scalar. The scalar multiple of A by k, denoted ………… will be the same size as A. …………………… The matrix (-1)A= -A called the …………… of A. Let A and B of the same size then: A - B= A +(-B)=C and: ……………………

Ch2_6 Example 2 Determine A + B, 3A, A + C, A-B Solution

Ch2_7 Definition A ……. matrix all of it’s elements are zero. If the zero matrix is of a square size n×n it will be denoted by. Theorem2.2: Let A,B,C be matrices, be scalars. Assume that the size of the matrices are such that the operations can be performed, let 0 be the zero matrix. Properties of matrix addition and scalar multiplication:

Ch2_8 Example 3 Compute the linear combination: for: Solution

Ch2_9 Multiplication of Matrices Definition 1) If the number of ……….. in A = the number of …….. in B. The product AB then exists. Let A: …….. matrix, B: ………. matrix, The product matrix C=AB is a ………. matrix. 2) If the number of ………. in A the number of …….. in B then The product AB ……………..

Ch2_10

Ch2_11 Note: Example 4 Let C = AB, Determine c 23.

Ch2_12 Example 5 Solution Note. In general, ……………

Ch2_13 Definition 1) A …….. matrix is a matrix in which all the elements are zeros. 2) A ……….. matrix is a square matrix in which all the elements ……………………………………... 3) An ……….. matrix is a diagonal matrix in which every element in the main diagonal is ……. Special Matrices

Ch2_14 Theorem 2.1 Let A be m  n matrix and O mn be the zero m  n matrix. Let B be an n  n square matrix. O n and I n be the zero and identity n  n matrices. Then: 1) A + O mn = O mn + A = ……. 2) BO n = O n B = ……… 3) BI n = I n B = ……… Example 6

Ch2_15 Let A, B, and C be matrices and k be a scalar. Assume that the size of the matrices are such that the operations can be performed. Properties of Matrix Multiplication 1. A(BC) = …………. Associative property of multiplication 2. A(B + C) = ………… Distributive property of multiplication 3. (A + B)C = ………… Distributive property of multiplication 4. AI n = I n A =……… (where I n is the identity matrix) 5. k(AB) = ………= ……… Note: AB  BA in general.Multiplication of matrices is not commutative. Theorem Algebraic Properties of Matrix Operations

Ch2_16 Example 7 Compute ABC. Solution

Ch2_17 In algebra we know that the following cancellation laws apply. If ab = ac and a  0 then ……….. If pq = 0 then ……….. or ………. However the corresponding results are not true for matrices. AB = AC ………………. that B = C. PQ = O ………………… that P = O or Q = O. Note : Example 8

Ch2_18 Powers of Matrices Theorem 2.3 If A is an n  n square matrix and r and s are nonnegative integers, then 1. A r A s = ………. 2. (A r ) s = ………. 3. A 0 = ……… (by definition) Definition If A is a square matrix and k is a positive integer, then

Ch2_19 Example 9 Solution Example 10 Simplify the following matrix expression. Solution

Ch2_20 Idempotent and Nilpotent Matrices Definition A square matrix A is said to be: ………………. if ………….. ………………. if there is a positive integer p s.t ……….… The least integer p such that A p =0 is called the ……………………. of the matrix. Example 11

Ch2_ Symmetric Matrices Definition The …………….. of a matrix A, denoted ………, is the matrix whose ………….. are the ………. of the given matrix A. Example 12 Determine the transpose of the following matrices:

Ch2_22 Theorem : Properties of Transpose Let A and B be matrices and k be a scalar. Assume that the sizes of the matrices are such that the operations can be performed. 1. (A + B) t = ………...Transpose of a sum 2. (kA) t =...…Transpose of a scalar multiple 3. (AB) t = ………... Transpose of a product 4. (A t ) t = ………...

Ch2_23 Symmetric Matrix match Definition Let A be a square matrix: 1) If ………... then A called ………………... matrix. 2) If ………... then A called ………………... matrix. Example 13 symmetric matrices

Ch2_24 Example 14 Proof Let A and B be symmetric matrices of the same size. C = aA+bB, a,b are scalars. Prove that C is symmetric.

Ch2_25 Example 15 Proof Let A and B be symmetric matrices of the same size. Prove that the product AB is symmetric if and only if AB = BA.

Ch2_26 Example 16 Proof Let A be a symmetric matrix. Prove that A 2 is symmetric.

Ch2_27 Definition Let A be a square matrix. The ………… of A denoted by …….. is the …………………………………. of A. Let A and B be matrices and k be a scalar. Assume that the sizes of the matrices are such that the operations can be performed. 1.tr(A + B) = ………………….. 2.tr(kA) = …………. 3.tr(AB) = ………… 4.tr(A t ) = ………….. Theorem : Properties of Trace.