problem-solving-with-algorithms-and-data-structure-using-python 中文版

这本书是第一部连贯的讲述遗传算法在电磁学上的应用。 这本书的构造是以电磁学的论题为基础的，因此很清楚的可以看到现在研究的几大领域。 第一章讲述的是局部优化方法（local optimization）的一些性质，并且讲清楚了他们的缺点，从而可以看出遗传算法的优点。 第二章简单的讲述了遗传算法的特点，覆盖了遗传算法的大部分区域。两个特点需要注意：第一个是例举MATLAB的程序来讲述遗传算法的过程；第二个是例举电磁设计的过程，包括多目标，从数据库中选取优化参数等方法。 第三章讲了遗传算法应用在天线阵列优化的两个例子。利用这两个例子介绍了遗传算法。 第四章是本书的主体。他具体的介绍了GA用于天线阵列优化上。 第五章讨论了遗传算法用于自适应或者是智能天线。也就是把遗传算法当做自适应算法。 第六章讨论了遗传算法用于线天线。其中包括加载线天线，遗传算法天线，曲线天线和八木天线。 第七章和第八章进一步给出了遗传算法优化的例子，第七章是优化口径天线和微带天线，第八章优化周期结构和电磁带隙结构。 第九章给出了遗传算法，PSO算法的参数选择，并提出了多目标优化的问题。 最后这本书给出了编码的方法。

使用基因算法和模糊的多目标优化方面的英文原版书籍!

vAlgorithms Data Structures=Programs.Algorithms Data Structures=Programs.Algorithms Data Structures=Programs.

Python Algorithms - Mastering Basic Algorithms in the Python Language

讲解python算法相关的书

机器学习的信息理论基础。 我移除了里面添加的链接等信息，可以直接打印成很干净的书。

Data_structures_algorithms_tutorial

This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. Features: includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface; provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples; offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author; presents a primer on Python for those from a different language background. Table of Contents Chapter 1 Python Programming 101 Chapter 2 Computational Complexity Chapter 3 Recursion Chapter 4 Sequences Chapter 5 Sets and Maps Chapter 6 Trees Chapter 7 Graphs Chapter 8 Membership Structures Chapter 9 Heaps Chapter 10 Balanced Binary Search Trees Chapter 11 B-Trees Chapter 12 Heuristic Search Appendix A: Integer Operators Appendix B: Float Operators Appendix C: String Operators and Methods Appendix D: List Operators and Methods Appendix E: Dictionary Operators and Methods Appendix F: Turtle Methods Appendix H: Complete Programs