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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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