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突然单相短路无阻尼绕组用matlab编程(Single-phase sudden short-circuit without damping windings)

MATLAB code for convex hull program

说明：  matlab 直接序列扩频中对于高斯白噪声的抗干扰仿真仿真程序(matlab in direct sequence spread spectrum interference for the simulation of Gaussian white noise simulation program)

基于simulink的RS编码译码，分析其误码率，并画出它的性能曲线。(RS code decoding based on simulink, analyze the bit error rate, and draw its performance curve.)

meanshift算法的中文入门资料，介绍的很详细(meanshift s Algorithm Chinese introduction material, introduction is very detailed)

霍夫曼编码 是一种瞬时的、唯一可解码的分组编码。 MATLAB源文件，用于图像压缩 ，可添加到MATLAB路径，直接调用！(Huffman coding is a transient, only the encoding can be decoded packet. MATLAB source files, for image compression, can be added to the MATLAB path, directly call!)

《MATLAB神经网络超级学习手册》随书光盘，《MATLAB神经网络超级学习手册》以神经网络结构为主线，以学习算法为副线，结合各种实例，目的是使读者易看懂、会应用。本书是一本简明介绍MATLAB神经网络设计技能的综合性用书。《MATLAB神经网络超级学习手册》深入浅出，实例引导，讲解详实，既可以作为高等院校理工科的研究生、本科生的教材，也可作为广大科研工程技术人员的参考用书。( MATLAB neural network super learning Handbook CD with the book, MATLAB neural network super learning manual to the neural network structure of the main line, as Vice-line learning algorithm, combined with a variety of examples is intended to enable readers to easily understand, will be applied. This book is a brief introduction to MATLAB neural network design skills and comprehensive book. MATLAB neural network super learning Handbook in layman s language, examples guidance, detailed explanation, either as colleges of science and engineering graduate students, undergraduate teaching, but also can be used as a reference the majority of scientific engineering and technical personnel of the book.)

蚁群算法是受真实的蚂蚁群体行为启发而得出的一类仿生算法。采用蚁群算法，设计好蚁群系统，利用MATLAB进行仿真，解决函数优化问题。(Ant colony algorithm is inspired by real ants swarm behavior and it is concluded that the category of bionic algorithm. Using ant colony algorithm, design good ant colony system, use of MATLAB simulation, to solve the function optimization problem.)

AR1000 FM module datasheet and application notes

Comparison of the performances of the LS and the MMSE channel estimators