Finite-Dimensional Linear Algebra

Regular price €69.99
A01=Mark S. Gockenbach
Adjacent Transpositions
Age Group_Uncategorized
Age Group_Uncategorized
Algebraic Multiplicity
approximation
Author_Mark S. Gockenbach
automatic-update
Category1=Non-Fiction
Category=PBF
Category=PH
Category=PSA
Cauchy Sequence
combinatorics
computational mathematics
Continuous Piecewise
Continuous Piecewise Linear Functions
COP=United Kingdom
Delivery_Pre-order
diagonalization
differential equations
eigenvalues
eq_isMigrated=2
eq_non-fiction
eq_science
Euclidean Algorithm
finite-dimensional linear algebra
Gaussian Elimination
Geometric Multiplicity
Greatest Common Divisor
Induced Matrix Norm
Initial BFS
inner products
Interpolation Nodes
Jordan canonical form
Language_English
Linear Operator
Linear Operator Equation
linear operators
Linearly Independent
LU Factorization
Normed Vector Space
numerical linear algebra
optimization
ordinary differential equations (ODEs)
PA=Not yet available
Piecewise Linear
Piecewise Linear Functions
Price_€50 to €100
PS=Forthcoming
QR Algorithm
QR Factorization
Row Interchanges
singular value decomposition (SVD)
Smith Normal Form
softlaunch
spectral theory
symmetric matrices
Vector Space
vector spaces

Product details

  • ISBN 9781032917856
  • Weight: 1250g
  • Dimensions: 156 x 234mm
  • Publication Date: 14 Oct 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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Linear algebra forms the basis for much of modern mathematics—theoretical, applied, and computational. Finite-Dimensional Linear Algebra provides a solid foundation for the study of advanced mathematics and discusses applications of linear algebra to such diverse areas as combinatorics, differential equations, optimization, and approximation.

The author begins with an overview of the essential themes of the book: linear equations, best approximation, and diagonalization. He then takes students through an axiomatic development of vector spaces, linear operators, eigenvalues, norms, and inner products. In addition to discussing the special properties of symmetric matrices, he covers the Jordan canonical form, an important theoretical tool, and the singular value decomposition, a powerful tool for computation. The final chapters present introductions to numerical linear algebra and analysis in vector spaces, including a brief introduction to functional analysis (infinite-dimensional linear algebra).

Drawing on material from the author’s own course, this textbook gives students a strong theoretical understanding of linear algebra. It offers many illustrations of how linear algebra is used throughout mathematics.

Mark S. Gockenbach is a professor and chair of the Department of Mathematical Sciences at Michigan Technological University.