电力系统分析之短路电流计算

说明：  基于ΤΕΧ的排版系统，由美国计算机学家莱斯利·兰伯特（Leslie Lamport）在20世纪80年代初期开发，利用这种格式，即使使用者没有排版和程序设计的知识也可以充分发挥由TeX所提供的强大功能，能在几天，甚至几小时内生成很多具有书籍质量的印刷品。(LaTeX is a high-quality typesetting system; it includes features designed for the production of technical and scientific documentation.)

USFULL FOR eye detection

说明：  先进控制策了 模型预测控制（MPC）的经典书籍分享(Classic books on model predictive control)

Mathematica Package for Analysis and Control of Chaos

almost for every person in the world are free to use, and can run on most types of computer.

说明：  《电力电子系统建模及控制》是徐德鸿编著的一本书籍，该书重点介绍电力电子系统的动态模型的建立方法和控制系统的设计方法。("Modeling and Control of Power Electronic Systems" is a book edited by Xu Dehong. This book focuses on the establishment of dynamic models of power electronic systems and the design methods of control systems.)

说明：  第一本编程书教你编程，一本不需要编程语言的编程书。(The first programming book teaches you to program, a programming book that doesn't require a programming language.)

阿呆正传，喜欢的可以看下，都是源代码，供参考学习(a small game)

有关matlab编程算法的详细介绍，包括matlab中所用的各种函数以及各种代码示例(A detailed introduction to matlab programming algorithms, including various functions used in MATLAB and examples of various code examples)

说明：  Python数据挖掘入门与实践 本书作为数据挖掘入门读物，介绍了数据挖掘的基础知识、基本工具和实践方法，通过循序渐进地讲解算法，带你轻松踏上数据挖掘之旅。本书采用理论与实践相结合的方式，呈现了如何使用决策树和随机森林算法预测美国职业篮球联赛比赛结果，如何使用亲和性分析方法推荐电影，如何使用朴素贝叶斯算法进行社会媒体挖掘，等等。本书也涉及神经网络、深度学习、大数据处理等内容。本书面向愿意学习和尝试数据挖掘的程序员。(Introduction and practice of Python data mining As a primer on data mining, this book introduces the basic knowledge, basic tools and practical methods of data mining. By step-by-step explanation of the algorithm, you can easily embark on the journey of data mining. This book uses a combination of theory and practice, showing how to use the decision tree and random forest algorithm to predict the results of the American professional basketball league game, how to use the affinity analysis method to recommend movies, how to use the naive Bayesian algorithm for social media mining ,and many more. This book also covers neural networks, deep learning, big data processing and more. This book is for programmers who are willing to learn and experiment with data mining.)