数值优化学习资料

Burden Faires 写的经典数值分析教材，第九版，非扫描版

Numerical Methods Using MATLAB第四版,作者是 Mathews 和 Fink，英文版 文字版非扫描版.

包含机械出版社中译版（高清扫描）和英文原版，非常适合学习的数值分析教材。

这里面包含Numerical Methods Using MATLAB_Mathews_4th中英和答案pdf，需要的同学可以拿去，帮助更多学习算法的同学

Numerical Methods in Engineering with Python is a text for engineering students and a reference for practicing engineers, especially those who wish to explore the power and efficiency of Python. The choice of numerical methods was based on their relevance to engineering problems. Every method is discussed thoroughly and illustrated with problems involving both hand computation and programming. Computer code accompanies each method and is available on the book web site. This code is made simple and easy to understand by avoiding complex book-keeping schemes, while maintaining the essential features of the method Python was chosen as the example language because it is elegant, easy to learn and debug, and its facilities for handling arrays are unsurpassed. Moreover, it is an open-source software package that can be downloaded freely on theweb. Python is a great language for teaching scientific computation.

TOPICS Chapters 1-6 provide coverage of applied linear algebra sufficient for reading the remainder of the book. Chapter 1: Matrices The chapter introduces matrix arithmetic and the very important topic of linear transformations. Rotation matrices provide an interesting and useful example of linear transformations. After discussing matrix powers, the concept of the matrix inverse and transpose concludes the chapter. Chapter 2: Linear Equations This chapter introduces Gaussian elimination for the solution of linear systems Ax = b and for the computation of the matrix inverse. The chapter also introduces the relationship between the matrix inverse and the solution to a linear homogeneous equation. Two applications involving a truss and an electrical circuit conclude the chapter. Chapter 3: Subspaces This chapter is, by its very nature, somewhat abstract. It introduces the concepts of subspaces, linear independence, basis, matrix rank, range, and null space. Although the chapter may challenge some readers, the concepts are essential for understanding many topics in the book, and it should be covered thoroughly. Chapter 4: Determinants Although the determinant is rarely computed in practice, it is often used in proofs of important results. The chapter introduces the determinant and its computation using expansion byminors and by rowelimination. The chapter ends with an interesting application of the determinant to text encryption. Chapter 5: Eigenvalues and Eigenvectors This is a very important chapter, and its results are used throughout the book. After defining the eigenvalue and an associated eigenvector, the chapter develops some of their most important properties, including their use in matrix diagonalization. The chapter concludes with an application to the solution of systems of ordinary differential equations and the problem of ranking items using eigenvectors. Chapter 6: Orthogonal Vectors and Matrices This chapter introduces the inner product and its associati

Numerical Recipes - The Art of Scientific Computing(3rd) 英文无水印pdf 第3版 pdf所有页面使用FoxitReader和PDF-XChangeViewer测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 本资源转载自网络，如有侵权，请联系上传者或csdn删除

这是本有关统计学的书籍，主要介绍数值分析的思想在统计中的应用。

数值分析第二版 英文版 非扫描 pdf 数值分析第二版 Numerical Analysis 2nd Timothy Sauer