Applied Linear Algebra

ISBN-10: 0131473824
ISBN-13: 9780131473829
Edition: 2005
List price: $209.80
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Description: For in-depth Linear Algebra courses that focus on applications. This text aims to teach basic methods and algorithms used in modern, real problems that are likely to be encountered by engineering and science students - and to foster understanding of  More...

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Book details

List price: $209.80
Copyright year: 2005
Publisher: Prentice Hall PTR
Publication date: 1/10/2005
Binding: Paperback
Pages: 736
Size: 8.00" wide x 10.00" long x 1.25" tall
Weight: 4.070
Language: English

For in-depth Linear Algebra courses that focus on applications. This text aims to teach basic methods and algorithms used in modern, real problems that are likely to be encountered by engineering and science students - and to foster understanding of why mathematical techniques work and how they can be derived from first principles. No text goes as far (and wide) in applications. The authors present applications hand in hand with theory, leading students through the reasoning that leads to the important results, and provide theorems and proofs where needed. Because no previous exposure to linear algebra is assumed, the text can be used for a motivated entry-level class as well as advanced undergraduate and beginning graduate engineering/applied math students.

Linear Algebraic Systems
Solution of Linear Systems
Matrices and Vectors
Gaussian Elimination-Regular Case
Pivoting and Permutations
Matrix Inverses
Transposes and Symmetric Matrices
Practical Linear Algebra
General Linear Systems
Determinants
Vector Spaces and Bases
Vector Spaces
Subspaces
Span and Linear Independence
Bases
The Fundamental Matrix Subspaces
Graphs and Incidence Matrices
Inner Products and Norms
Inner Products
Inequalities
Norms
Positive Definite Matrices
Completing the Square
Complex Vector Spaces
Minimization and Least Squares Approximation
Minimization Problems
Minimization of Quadratic Functions
Least Squares and the Closest Point
Data Fitting and Interpolation
Orthogonality
Orthogonal Bases
The Gram-Schmidt Process
Orthogonal Matrices
Orthogonal Polynomials
Orthogonal Projections and Least Squares
Orthogonal Subspaces
Equilibrium
Springs and Masses
Electrical Networks
Structures
Linearity
Linear Functions
Linear Transformations
Affine Transformations and Isometries
Linear Systems
Adjoints
Eigenvalues
Simple Dynamical Systems
Eigenvalues and Eigenvectors
Eigenvector Bases and Diagonalization
Eigenvalues of Symmetric Matrices
Singular Values
Incomplete Matrices and the Jordan Canonical Form
Linear Dynamical Systems
Basic Solution Methods
Stability of Linear Systems
Two-Dimensional Systems

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