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Applied Engineering Analysis - slides for class teaching* Chapter 4 Linear Algebra and Matrices * Based on the book of “Applied Engineering Analysis”, by Tai-Ran Hsu, published by John Wiley & Sons, 2018. (ISBN 9781119071204) (Chapter 4 Linear Algebra and Matrices) 1 © Tai-Ran Hsu Chapter Learning Objectives Linear algebra and its applications Forms of linear functions and linear equations Expression of simultaneous linear equations in matrix forms Distinction between matrices and determinants Different forms of matrices for different applications Transposition of matrices Addition, subtraction and multiplication of matrices Inversion of matrices Solution of simultaneous equations using matrix inversion method Solution of large numbers of simultaneous equations using Gaussian elimination method Eigenvalues and Eigenfunctions in engineering analysis 2 4.1 Introduction to Linear Algebra and Matrices Linear algebra is concerned mainly with: Systems of linear equations, Matrices, Vector space, Linear transformations, Eigenvalues, and eigenvectors. Linear and Non-linear Functions and Equations: Linear equations: Linear -4x + 3x –2x + x = 0 functions: 1 2 3 4 where x , x , x and x are 1 2 3 4 unknown quantities Examples of Nonlinear Equations: Simultaneous linear equations: 2 3 84xx x12 4x1 3x2 2x3 x4 0 123 26xx x3 or x2 + y2 = 1 123 xx22x or xy = 1 123 or sinx = y where x1, x2 and x3 are unknown quantities 3 4.2 Determinants and Matrices Both determinants and matrices are logical and convenient representations of large sets of real numbers or variables and vectors involved in engineering analyses. These large sets of real numbers, variables and vector quantities are arranged in arrays of rows and columns: a a a a 11 12 13 1n a21 a22 a23 a2n a31 a32 a33 a3n am1 am2 am3 amn in which a , a ,………………….., a represent group of data, with m=row number, 11 12 mn n = column number, and m = 1,2,3,….,m and n = 1,2,3,…..,n 4
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