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隨著計算機技術的發展，綫性代數課程的重要性越來越突齣。同時，現代軟件已經為顯著改進授課方式提供瞭可能。本書作者多年講授綫性代數課程，並在教學過程中不斷探索更利於學生理解的新教學方法，從而使本書更加適閤作為綫性代數課程的教材。

在第8版中，擴充瞭矩陣代數的知識，新增瞭嚮量積、實舒爾分解的內容，並增加瞭130多道新練習。

本書主要特點

 理論與應用有機結閤。大量的實際應用貫穿於理論講解的始終，體現瞭綫性代數在各個領域中的廣泛應用。

 示例豐富。便於讀者理解相關的定義及原理，增強瞭讀者學習的興趣。

 習題安排錯落有緻。每一節的後麵給齣大量的習題，各章後麵還有測試題，使學生有更多的演練機會，達到觸類旁通的效果。

 緊密結閤數學工具MATLAB。每章的後麵都有基於MATLAB的上機練習，並在附錄中介紹瞭MATLAB的基本用法。

Steven J. Leon 1971年於密歇根州立大學數學係獲得博士學位，現為馬薩諸塞大學達特茅斯分校數學係首席教授，ILAS（國際綫性代數協會）、MAA（美國數學學會）和SIAM（美國工業與應用數學協會）成員。他主要從事科學計算、綫性代數和應用數學等領域的研究。

Contents
Preface iii
Matrices and Systems of Equations 1
1.1 Systems of Linear Equations 1
1.2 Row EchelonForm 11
1.3 Matrix Arithmetic 27
1.4 Matrix Algebra 44
1.5 Elementary Matrices 58
1.6 Partitioned Matrices 68
MATLAB R Exercises 77
ChapterTestA 81
ChapterTestB 82
2 Determinants 84
2.1 The Determinant of a Matrix 84
2.2 Properties of Determinants 91
2.3. AdditionalTopics and Applications 98
MATLAB Exercises 106
ChapterTestA 108
ChapterTestB 108
3 Vector Spaces 110
3.1 Definition and Examples 110
3.2 Subspaces 117
3.3 Linear Independence 127
3.4 Basis and Dimension 138
3.5 Change of Basis 144
3.6 Row Space and Column Space 154
MATLAB Exercises 162
ChapterTestA 164
ChapterTestB 164
4 Linear Transformations 166
4.1 Definition and Examples 166
4.2 Matrix Representationsof LinearTransformations 175
4.3 Similarity 189
MATLAB Exercises 195
ChapterTestA 196
ChapterTestB 197
5 Orthogonality 198
5.1 The Scalar Product in Rn 199
5.2 Orthogonal Subspaces 214
5.3 Least Squares Problems 222
5.4 Inner Product Spaces 232
5.5 Orthonormal Sets 241
5.6 The Gram–Schmidt Orthogonalization Process 259
5.7 Orthogonal Polynomials 269
MATLAB Exercises 277
ChapterTestA 279
ChapterTestB 280
6 Eigenvalues 282
6.1 Eigenvalues and Eigenvectors 283
6.2 Systems of Linear Differential Equations 296
6.3 Diagonalization 307
6.4 Hermitian Matrices 324
6.5 The SingularValue Decomposition 337
6.6 QuadraticForms 351
6.7 Positive Definite Matrices 364
6.8 Nonnegative Matrices 372
MATLAB Exercises 378
ChapterTestA 384
ChapterTestB 384
7 Numerical Linear Algebra 386
7.1 Floating-Point Numbers 387
7.2 Gaussian Elimination 391
7.3 Pivoting Strategies 398
7.4 Matrix Norms and Condition Numbers 403
7.5 Orthogonal Transformations 417
7.6 The Eigenvalue Problem 428
7.7 Least Squares Problems 437
MATLAB Exercises 448
Chapter Test A 454
Chapter Test B 454
8 Iterative Methods Web.
9 Canonical Forms Web.
Appendix: MATLAB 456
Bibliography 468
Answers to Selected Exercises 471
Index 485
. Optional sections. These sections are not prerequisites for any other sections of the book.
. Web: The supplemental Chapters 8 and 9 can be downloaded from the internet. See the section of the Preface on supplemental Web materials.
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