From the table of contents: K-modules and linear transformations; Linear independence, spanning, bases, and dimension; Coordinates, column vectors, and matrices; Eigenstuff; Multilinear algebra and tensors; Inner-product spaces; Applications.
The text is an attempt to provide a way to understand the ideas without the students already having the mathematical maturity that a good undergraduate analysis course could provide.
The book is a collection of solved problems in linear algebra, this fourth volume covers quadratic equations in two or three variables.
Tutorial describing many of the standard numerical methods used in Linear Algebra.
Topics include Gaussian Elimination, LU and QR Factorizations, The Singular Value Decomposition, Eigenvalues and Eigenvectors via the QR Method, etc.
This book is a continuation of the book n-linear algebra of type I.
Most of the properties that could not be derived or defined for n-linear algebra of type I is made possible in this new structure which is introduced in this book.n-Linear Algebra of type I introduced in this book finds applications in Markov chains and Leontief economic models.
All examples are solved, and the solutions usually consist of step-by-step instructions.
The book is a collection of solved problems in linear algebra.
It includes a range of theorems and applications in different branches of linear algebra, such as linear systems, matrices, operators, etc.
This book discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices.