Introduction to Linear Algebra

出版者:Wellesley-Cambridge Press

作者:Gilbert Strang

页数:600

出版时间:2016-8-31

价格:GBP 64.99

装帧:Hardcover

isbn号码:9780980232776

作者简介

Gilbert Strang was an undergraduate at MIT and a Rhodes Scholar at Balliol College, Oxford. His Ph.D. was from UCLA and since then he has taught at MIT. He has been a Sloan Fellow and a Fairchild Scholar and is a Fellow of the American Academy of Arts and Sciences. He is a Professor of Mathematics at MIT, an Honorary Fellow of Balliol College, and a member of the National Academy of Sciences. Professor Strang has published eleven books:

Differential Equations and Linear Algebra (2014)

Introduction to Linear Algebra (1993,1998,2003,2009)

Linear Algebra and Its Applications (1976,1980,1988,2005)

An Analysis of the Finite Element Method, with George Fix (1973, 2008)

Introduction to Applied Mathematics (1986)

Calculus (1991)

Wavelets and Filter Banks, with Truong Nguyen (1996)

Linear Algebra, Geodesy, and GPS, with Kai Borre (1997)

Computational Science and Engineering (2007)

Essays in Linear Algebra (2012)

Algorithms for Global Positioning, with Kai Borre (2012)

He was the President of SIAM during 1999 and 2000, and Chair of the Joint Policy Board for Mathematics. He received the von Neumann Medal of the US Association for Computational Mechanics, and the Henrici Prize for applied analysis. The first Su Buchin Prize from the International Congress of Industrial and Applied Mathematics, and the Haimo Prize from the Mathematical Association of America, were awarded for his contributions to teaching around the world. His home page is math.mit.edu/~gs/ and his video lectures on linear algebra and on computational science and engineering are on ocw.mit.edu (mathematics/18.06 and 18.085).

目录信息

1 Introduction to Vectors
2 Solving Linear Equations
3 Vector Spaces and Subspaces
4 Orthogonality
5 Determinants
6 Eigenvalues and Eigenvectors
7 The Singular Value Decomposition (SVD)
8 Linear Transformations
9 Complex Vectors and Matrices
10 Applications
11 Numerical Linear Algebra
12 Linear Algebra in Probability & Statistics
· · · · · · (收起)

读后感

这本书写了有3种方法 1.直接通过高斯消元得阶梯阵，然后通过回带求得 2.直接通过公式x=A^(-1)*b求得 3.通过零空间的全解加上一个特解求得 觉得这三种方法之中，还是最原始的消元法最管用，或者说掌握怎么消元是最基本的技巧。 第一种方法中，如果是正方阵，还可消元的A=L...  

实在是很棒的一本教科书，我在教学当中接触到该书以后，不由自主就想把它翻译过来，毕竟多数读者用英语直接阅读还存在一些困难。历时一年完成了翻译，现在到了和出版社接洽的时候了。（本人已经和原作者进行了联系。）广大读者的支持将有助于本书的出版！  

还记得大四保研面试的时候，问的第一个问题是：讲一下奇异值分解的方法、应用和物理意义。面试之前我准备了一周，设想过很多种奇葩的场面，但是这个问题真把我问蒙了，我甚至不知道这是哪门课教的东西，完全不知道怎么答。支吾了大概10秒钟不知所云之后，我忍不住观察了一下老...  

这本书写了有3种方法 1.直接通过高斯消元得阶梯阵，然后通过回带求得 2.直接通过公式x=A^(-1)*b求得 3.通过零空间的全解加上一个特解求得 觉得这三种方法之中，还是最原始的消元法最管用，或者说掌握怎么消元是最基本的技巧。 第一种方法中，如果是正方阵，还可消元的A=L...  

用户评价

配合 MIT OCW 上 Gilbert 的 lecture 服用，妈妈再也不用担心我的线代学不会了

太棒了????

After being tired of 快速入门 “极限编程” 通过冒烟测试然后迅速淡忘，我选择建筑性地补习线性代数（为了学习机器学习）事实证明糟糕地表达和结构安排造成的隔阂远胜过母语和另一门语言之间地隔阂 国内教材真的太差了 授课顺序也很不合理

线性代数教材巅峰之作。你会知道什么叫深入浅出，原来数学课本可以读来如此舒适。

目前为止看过的最好的线性代数教材，可以很好的帮助读者建立对线性代数中的基础概念和概念之间相互联系的理解，章节布局由浅入深，环环相扣。稍有不足的是对定理的证明比较少。