1.

Record Nr.

UNINA9910460834003321

Autore

Penney Richard C.

Titolo

Linear algebra : ideas and applications / / Richard Penney

Pubbl/distr/stampa

Hoboken, New Jersey : , : Wiley, , 2016

©2016

ISBN

1-118-90962-3

Edizione

[Fourth edition.]

Descrizione fisica

1 online resource (513 p.)

Disciplina

512/.5

Soggetti

Algebras, Linear

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Includes index.

Nota di contenuto

Linear Algebra; Contents; Preface; Features of the Text; Acknowledgments; About the Companion Website; Chapter 1 Systems of Linear Equations; 1.1 The Vector Space of  Matrices;  The Space Rn;  Linear Combinations and Linear Dependence;  What Is a Vector Space?;  Why Prove Anything?;  Exercises; 1.1.1 Computer Projects;  Exercises; 1.1.2 Applications to Graph Theory I;  Self-Study Questions;  Exercises; 1.2 Systems;  Rank: The Maximum Number of Linearly Independent Equations;  Exercises; 1.2.1 Computer Projects;  Exercises; 1.2.2 Applications to Circuit Theory;  Self-Study Questions

Exercises1.3 Gaussian Elimination;  Spanning in Polynomial Spaces;  Computational Issues: Pivoting;  Exercises;  Computational Issues: Counting Flops; 1.3.1 Computer Projects;  Exercises;  Applications to Traffic Flow;  Self-Study Questions;  Exercises; 1.4 Column Space and Nullspace;  Subspaces;  Exercises;  Computer Projects;  Chapter Summary; Chapter 2 Linear Independence and Dimension; 2.1 The Test for Linear Independence;  Bases for the Column Space;  Testing Functions for Independence;  Exercises; 2.1.1 Computer Projects ;  Exercises; 2.2 Dimension;  Exercises; 2.2.1 Computer Projects

Exercises2.2.2 Applications to Differential Equations;  Exercises; 2.3 Row Space and the rank-nullity theorem;  Bases for the Row Space;  Summary;  Computational Issues: Computing Rank;  Exercises; 2.3.1 Computer Projects;  Exercises;  Chapter Summary; Chapter 3 Linear Transformations; 3.1 The Linearity Properties;  Exercises; 3.1.1



Computer Projects;  Exercises; 3.2 Matrix Multiplication (Composition);  Partitioned Matrices;  Computational Issues: Parallel Computing;  Exercises; 3.2.1 Computer Projects;  Exercises; 3.2.2 Applications to Graph Theory II;  Self-Study Questions;  Exercises

3.3 Inverses Computational Issues: Reduction versus Inverses;  Exercises; 3.3.1 Computer Projects;  Exercises; 3.3.2 Applications to Economics;  Self-Study Questions;  Exercises; 3.4 The LU Factorization;  Exercises; 3.4.1 Computer Projects;  Exercises; 3.5 The Matrix of a Linear Transformation;  Coordinates;  Application to Differential Equations;  Isomorphism;  Invertible Linear Transformations;  Exercises;  Computer Projects;  Exercises; Chapter Summary; Chapter 4 Determinants; 4.1 Definition of the Determinant; 4.1.1 The Rest of the Proofs;  Exercises; 4.1.2 Computer Projects

4.2 Reduction and Determinants Uniqueness of the Determinant;  Exercises; 4.2.1 Volume;  Exercises;  A Formula for Inverses;  Exercises;  Chapter Summary; Chapter 5 Eigenvectors and Eigenvalues; 5.1 Eigenvectors;  Exercises; 5.1.1 Computer Projects;  Exercises; 5.1.2 Application to Markov Processes;  Exercises; 5.2 Diagonalization;  Powers of Matrices;  Exercises; 5.2.1 Computer Projects;  Exercises; 5.2.2 Application to Systems of Differential Equations;  Exercises; 5.3 Complex Eigenvectors;  Complex Vector Spaces;  Exercises; 5.3.1 Computer Projects; 5.3 Exercises; Chapter Summary

Chapter 6 Orthogonality