Elementary Linear Algebra With Applications, 9Th Edition -

Elementary Linear Algebra, 8th Edition by Ron Larson | 467 pages Table of Contents 1. SYSTEMS OF LINEAR EQUATIONS. Introduction to Systems of Equations. Gaussian Elimination and Gauss-Jordan Elimination. Applications of Systems of Linear Equations. 2. MATRICES. Operations with Matrices. Properties of Matrix Operations. The Inverse of a Matrix. Elementary Matrices. Markov Chains. Applications of Matrix Operations. 3. DETERMINANTS. The Determinant of a Matrix. Evaluation of a Determinant Using Elementary Operations. Properties of Determinants. Applications of Determinants. 4. VECTOR SPACES. Vectors in Rn. Vector Spaces. Subspaces of Vector Spaces. Spanning Sets and Linear Independence. Basis and Dimension. Rank of a Matrix and Systems of Linear Equations. Coordinates and Change of Basis. Applications of Vector Spaces. 5. INNER PRODUCT SPACES. Length and Dot Product in Rn. Inner Product Spaces. Orthogonal Bases: Gram-Schmidt Process. Mathematical Models and Least Squares Analysis. Applications of Inner Product Spaces. 6. LINEAR TRANSFORMATIONS. Introduction to Linear Transformations. The Kernel and Range of a Linear Transformation. Matrices for Linear Transformations. Transition Matrices and Similarity. Applications of Linear Transformations. 7. EIGENVALUES AND EIGENVECTORS. Eigenvalues and Eigenvectors. Diagonalization. Symmetric Matrices and Orthogonal Diagonalization. Applications of Eigenvalues and Eigenvectors. 8. COMPLEX VECTOR SPACES (online). Complex Numbers. Conjugates and Division of Complex Numbers. Polar Form and Demoivre’s Theorem. Complex Vector Spaces and Inner Products. Unitary and Hermitian Spaces. 9. LINEAR PROGRAMMING (online). Systems of Linear Inequalities. Linear Programming Involving Two Variables. The Simplex Method: Maximization. The Simplex Method: Minimization. The Simplex Method: Mixed Constraints. 10. NUMERICAL METHODS (online). Gaussian Elimination with Partial Pivoting. Iterative Methods for Solving Linear Systems. Power Method for Approximating Eigenvalues. Applications of Numerical Methods.

a very good book for linear system throry

经典教材，讲述线性和非线性方面的优化问题。

This book is intended as a text covering the central concepts of practical optimization techniques. It is designed for either self-study by professionals or classroom work at the undergraduate or graduate level for students who have a technical background in engineering, mathematics, or science. Like the field of optimization itself, which involves many classical disciplines, the book should be useful to system analysts, operations researchers, numerical analysts, management scientists, and other specialists from the host of disciplines from which practical optimization applications are drawn. The prerequisites for convenient use of the book are relatively modest; the prime requirement being some familiarity with introductory elements of linear algebra. Certain sections and developments do assume some knowledge of more advanced concepts of linear algebra, such as eigenvector analysis, or some background in sets of real numbers, but the text is structured so that the mainstream of the development can be faithfully pursued without reliance on this more advanced background material.

Richard W. Cottle,Jong-Shi Pang,Richard E. Stone Paperback: 789 pages Publisher: Society for Industrial & Applied Mathematics (July 28, 2009) Language: English ISBN-10: 0898716861 ISBN-13: 978-0898716863 Product Dimensions: 6.8 x 1.6 x 9.7 inches 研究游戏物理引擎的同学不要错过啊。

线性模型 机器学习线性模型用于回归和分类

《线性代数引论》是MIT著名数学教授Gilbert Strang的经典之作，也是线性代数最为经典的教材之一。线性代数在科学和工程中具有重要地位，书中对线性代数的理解和把握精简到位，对与当初学而不懂的自己犹如醍醐灌顶。也希望大家能领略到学习的乐趣，只有真正理解了懂了才能不断前进并学以致用，网易公开课中有 Gilbert Strang 教授的课程，建议对照学习，必会有所收益。本书为高清第五版全英文，也是最新一版，请大家放心下载。

【达摩老生出品，必属精品，亲测校正，质量保证】 资源名：Locally Linear Embedding_LLE_Matlab代码_对研究Manifold Leanring有所帮助 资源类型：matlab项目全套源码 源码说明： 全部项目源码都是经过测试校正后百分百成功运行的，如果您下载后不能运行可联系我进行指导或者更换。 适合人群：新手及有一定经验的开发人员

linear system theory and design solution: chen qizong