Matlab 代码再现了 SG Yiantsios 和 BG Higgins 中给出的剪切模式色散曲线，“两种叠加流体的平面泊肃叶流的线性稳定性”。 流体物理学 31, 3225-3238 (1988)。

Christofides算法 Christofides算法是一种算法，用于在距离形成度量空间（它们对称且服从三角形不等式）的情况下，找到旅行商问题的近似解。 它是一种近似算法，可确保其解在最佳解长度的3/2范围内，并以Nicos Christofides的名字命名，后者于1976年发布。截至2017年，这是具有被证明对一般度量空间旅行商问题，但更好的近似值是已知的一些特殊情况下， 算法的基本步骤： 查找最小生成树（T） 在T中以奇数（O）查找顶点 找到最小的重量匹配（M）边到T 使用M和T的边缘建立欧拉回路 通过跳过重复的顶点来建立哈密顿回路 Python实现 在文件christofid

C#开发中一些问题的解决办法，经过了一些整理，有些问题只有实践了才知道.

内含三种翻译工具翻译的文章，以及英汉对照

Inverse Problem Theory and Methods for Model Parameter Estimation （模型参数估计的反问题理论与方法） 作者：(意大利)(Albert Tarantola)塔兰托拉 PDF格式，英文。

Complete Algorithms for Cooperative Pathfinding Problems

这只是解决问题的示例，大部分来自Leetcode，并提供使用Python的算法和数据结构。

node-problem-detector 镜像包 v0.8.7 版本

Inverse problems arise when we reconstruct a sharper image from a blurred one or reconstruct the underground mass density from measurements of the gravity above the ground. When we solve an inverse problem, we compute the source that gives rise to some observed data using a mathematical model for the relation between the source and the data. This book gives an introduction to the practical treatment of inverse problems by means of numerical methods, with a focus on basic mathematical and computational aspects. To solve inverse problems, we demonstrate that insight about them goes hand in hand with algorithms. Discrete Inverse Problems: Insight and Algorithms includes a number of tutorial exercises that give the reader hands-on experience with the methods, difficulties, and challenges associated with the treatment of inverse problems. It also includes examples and figures that illustrate the theory and algorithms. Audience This book is written for graduate students, researchers, and professionals in engineering and other areas that depend on solving inverse problems with noisy data. The aim is to provide readers with enough background that they can solve simple inverse problems and read more advanced literature on the subject. Contents Preface; List of Symbols; Chapter 1: Introduction and Motivation; Chapter 2: Meet the Fredholm Integral Equation of the First Kind; Chapter 3: Getting to Business: Discretizations of Linear Inverse Problems; Chapter 4: Computational Aspects: Regularization Methods; Chapter 5: Getting Serious: Choosing the Regularization Parameter; Chapter 6: Toward Real-World Problems: Iterative Regularization; Chapter 7: Regularization Methods at Work: Solving Real Problems; Chapter 8: Beyond the 2-Norm: The Use of Discrete Smoothing Norms; Appendix A: Linear Algebra Stuff; Appendix B: Symmetric Toeplitz-Plus-Hankel Matrices and the DCT; Appendix C: Early Work on 揟ikhonov Regularization? Bibliography; Index. About the Author Per Christian Hansen is Professor of Scientific Computing at the Technical University of Denmark. His publications include two other books on inverse problems, several MATLAB?packages, and many papers on inverse problems, matrix computations, and signal processing. His home page is http://www2.imm.dtu.dk/~pch/. To request an examination copy or desk copy of this book, please use our online request form at www.siam.org/catalog/adopt.php.

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