《Linear Algebra》是在教育部大力推進雙語教學(xué)的大背景下推出的，結(jié)合當(dāng)前開展線性代數(shù)課程雙語教學(xué)的實際情況，以教育部數(shù)學(xué)與統(tǒng)計學(xué)教學(xué)指導(dǎo)委員會制定的本課程教學(xué)基本要求為依據(jù)，同時兼顧線性代數(shù)的研究生入學(xué)統(tǒng)一考試大綱要求，該書的中文版為同名作者編寫的普通高等教育“十一五”國家級規(guī)劃教材。與中文版一樣，英文版教材突出現(xiàn)代代數(shù)學(xué)和離散數(shù)學(xué)的思想，著重講解線性代數(shù)的基本概念、基本理論和基本方法，尤其注重體現(xiàn)線性代數(shù)在各個領(lǐng)域中的廣泛應(yīng)用，將大量的相關(guān)實例融合貫穿于理論、方法的講解中，將經(jīng)典和現(xiàn)代代數(shù)學(xué)的思想與離散數(shù)學(xué)的方法闡述得更為具體、實用。
《Linear Algebra》內(nèi)容包括線性代數(shù)方程組、矩陣、行列式、矩陣的秩和線性方程組的解、向量空間初步、矩陣的特征值問題和線性變換等共7章。全書取材的深廣度合適，注重聯(lián)系應(yīng)用，強調(diào)數(shù)學(xué)建模的融入，符合大學(xué)本科教學(xué)對本門課程的教學(xué)要求與實際需要�！禠inear Algebra》的起點較低、知識系統(tǒng)、詳略得當(dāng)、舉例豐富、講解透徹、難度適宜、思路清晰、易教易學(xué)，有利于培養(yǎng)學(xué)生用線性代數(shù)的思維方法去分析問題、解決問題，并注意激發(fā)學(xué)生學(xué)習(xí)的興趣和主動性。
英文版教材邀請了在美國任教的華裔學(xué)者共同編寫、審定，在文字表述方面，英文語言簡單易懂，寫作風(fēng)格簡約，可供普通高等學(xué)校工科類、理科類（非數(shù)學(xué)專業(yè)）、經(jīng)濟管理類有關(guān)專業(yè)的線性代數(shù)課程雙語教學(xué)使用。
Linear algebra is a fundamental part of modern mathematics which is concerned withthe study of systems of linear equations, matrices, vectors, vector spaces and lineartransformations. In addition to its own charm in mathematics, the applications of lin-ear algebra have appeared in many fields of the natural sciences, social sciences,computer sciences, statistics and economics, and are spreading more rapidly than anyother time in the past due to the advancement of the computer technology. Linear al-gebra has become a successful part of mathematical language. Motivated by the call of the bilingual teaching in higher education in China, thisbook is translated, with some addition and modification, from the second edition ofthe book \"Linear Algebras\" by Zhifeng Hao, Guorui Xie and Guoqiang Wang pub-lished in 2003, and from its modified edition published in 2008. The book targetsundergraduate students majoring in engineering, natural sciences and economics,who are expected to master essential concepts and skills of linear algebra in a one-semester course. The organization of this book is motivated by the needs of understand-ing and abilities of using the basic knowledge of linear algebra. Systems of linearequations are introduced and studied first, followed by logically matrices, determinantsand vector spaces. The discussions of eigenvalue problems and linear transformationsend the whole course at a higher level of understanding and abstraction of linear alge-bra, yet the main theme imbedded in the whole book is the theory of systems of linearequations. Our idea regarding the layout of the material is that each topic should befully developed, the connection with systems of linear equations should be madeclear, and enough examples and exercises should be available for supporting the un-derstanding. This arrangement is based on our experiences in teaching linear algebrafor more than ten years. This course suggests that students are motivated and encour-aged more if they see the connections, have enough practices, and progress with abetter and deeper understanding at each step. In addition, there are three other ped-agogical features which can be used to benefit students.
Chapter 1 System of Linear Equations and Elimination Method
1.1 Solving System of Linear Equations with Elimination Method
1.1.1 Linear System with Two Unknowns
1.1.2 Gauss-Jordan Elimination Method
1.2 Applications
Practice 1
Chapter 2 Matrices
2.1 Basic Concepts
2.1.1 Matrices
2.1.2 Special Matrices
2.1.3 Problems Related to Matrices
2.2 Basic Operations
2.2.1 Definitions
2.2.2 Rules of Operations
2.2.3 Applications
2.3 Matrix Inverses
2.3.1 lnvertible Matrices
2.3.2 Orthogonal Matrices
2.4 Blocks and Sub-matrices
2.4.1 Block Operations
2.4.2 Column Blocks
2.4.3 Sub-matrices
2.5 Elementary Operations and Elementary Matrices
2.5.1 Definitions and Properties
2.5.2 Equivalent Normal Form for Matrices
2.5.3 Invertible Matrices Revisit
2.5.4 Unique solution for n x n linear systems
2.6 Applications（Input - output Analysis）
Practice 2
Chapter 3 Determinants
3.1 Definitions and Properties of Determinants
3.1.1 Definitions
3.1.2 Propertie
3.2 Evaluation of Determinants
3.3 Applications
3.3.1 Adjugate Matrices and Inverse Formula
3.3.2 Cramers Rule
3.3.3 Summary
Practice 3
Chapter 4 Rank of a Matrix and Solutions for Linear Systems
4.1 Rank of a Matrix
4.1.1 Concepts
4.1.2 Computations
4.2 Solutions of Linear Systems
4.2.1 Homogeneous Systems
4.2.2 Non-homogeneous Systems
Practice 4
Chapter 5 Vector Spaces
5.1 Concepts
5.2 Linear Dependence and Linear Independence
5.2.1 Concepts
5.2.2 Properties
5.2.3 Rank of a Set of Vectors
5.2.4 Row and Column Ranks of a Matrix
5.3 Bases and Dimensions of Vector Spaces
5.3.1 Bases and Dimensions
5.3.2 Revisit Solutions for Linear Systems
5.4 Inner Products
5.4.1 Review
5.4.2 Inner Products and Orthogonal Matrices
5.4.3 Four Basic Subspaces
Practice 5
Chapter 6 Eigenvalues
6.1 Eigenvalues and Eigenvectors
6.2 Diagonalizations
6.2.1 Similar Matrices and Diagonal Forms
6.2.2 Applications
6.3 Real Symmetric Matrices and Quadratic Forms
6.3..1 Canonical Forms for Real Symmetric Matrices
6.3.2 Quadratic Forms
6.3.3 Quadratic Expressions and Their Canonical Forms
6.4 Positive Definite Matrices and Classification of Quadratic Forms
6.4.1 Positive Definite Matrices
6.4.2 Optimization
6.4.3 Generalized Eigenvalue Problems
Practice 6
Chapter 7 Linear Transformations
7.1 Basic Concepts of Linear Transformations
7.1.1 Linear Transformations
7.1.2 Range and Kernel for a Linear Transformation
7.2 Linear Transformations and Matrices
7.2.1 Coordinate Vectors
7.2.2 The Matrix Representations for Linear Transformations
7.2.3 Engenvalues and Eigenvectors of a Linear Transformation
Practice 7
References
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