电子书：应用线性代数导论——向量、矩阵和最小二乘法

                                                                                                                                                                                       

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摘要

 

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This book will be published in 2018 by Cambridge University Press, It is used as the textbook for the course EE103 (Stanford) and EE133A (UCLA), where you will find additional related material. Some of the book exercises also appear in the set of additional exercises below; we'll be sorting that out soon.

Stephen Boyd & Lieven Vandenberghe

Download

Copyright in this book is held by Cambridge University Press, who have kindly agreed to allow us to keep the book available on the web.

• Book (pdf file)

• Additional exercises for Vectors, Matrices, and Least Squares (DRAFT)

The lecture slides follow the organization of the textbook. The (book) links that follow some of the lecture slides take you to the associated chapter or section of the book.

• Introduction

• Vectors (book) (quiz)

• Linear functions (book) (quiz)

• Norm and distance (book) (quiz)

• Clustering (book) (quiz) (k-means visualizer)

• Linear independence (book) (quiz)

• Matrices (book) (quiz)

• Matrix examples (book)

• Linear equations (book) (quiz)

• Linear dynamical systems (book) (code)

• Matrix multiplication (book) (quiz)

• Matrix inverses (book) (quiz)

• Least squares (book) (quiz)

• Least squares data fitting (book)

• Least squares classification (book)

• Multi-objective least squares (book)

• Constrained least squares (book)

• Constrained least squares applications (book)

• Portfolio optimization (book) (code)

• Linear quadratic control (book) (code) (demo)

• Linear quadratic state estimation (book)

• Nonlinear least squares (book)

• Constrained nonlinear least squares (book)

• Review

The slides below cover various applications. Of course, they may not make sense until we cover the needed material.

• Audio signals

• Ballistics (code)

• Document analysis

• Handwritten digit classification

• Image processing

• Regression (code)

• Steganography

• Time series

• Tomography (book) (tomography visualizer)

You should read our warning about crimes against matrices.

链接：

https://web.stanford.edu/~boyd/vmls/

讲义链接：

https://web.stanford.edu/class/ee103/lectures.html

原文链接：

https://m.weibo.cn/1402400261/4214329962236643

“完整内容”请点击【阅读原文】

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