process

基于matlab的有源功率因数校正仿真，含电路仿真图(Matlab-based simulation of active power factor correction, including circuit simulation map)

huffman coding implementation

独立成分分析（Independent Component Analysis, ICA）是近年来发展起来的一种有效的盲分离技术，最早是由法国学者Herault和Jutten于1986年提出。ICA方法的提出最初是用来解决“鸡尾酒会”问题，其过程可以归纳为，在源信号与传输通道参数均未知的情况下，仅根据源信号的统计特性，出现测信号恢复出源信号。ICA分析的关键在于根据一定的优化准则建立描述输出信号独立程度的优化判据，即目标函数，并设计相应的优化算法，寻求最优的分离矩阵，使得输出信号中各分量尽可能相互独立。采用ICA方法对信号进行盲分离时，可避免过多地受大能量噪声成分的影响，将部分小能量信号源识别出来。随着ICA技术的不断发展，目前ICA技术已经广泛应用于语音增强、音频识别、通信、医学信号处理、金融数据挖掘、图像消噪、数字水印、遥感等领域，并取得了一定的研究成果。(Independent Component Analysis (ICA) Component ini order, developed in recent years is a kind of effective separation technology, originally from French scholars Herault and Jutten in 1986. The proposed method is initially ICA to solve the "cocktail" problem, the process can be divided into, in the source signal transmission channels and in the case of unknown parameters according to the source of the signals, and the statistical characteristics of recovering the source signal. According to the analysis of the ICA key lies in the establishment of optimal criteria described the output signal of the independent, objective function optimization criterion, and the corresponding optimization algorithm, the optimum )

利用K均值算法对7个波段的TM遥感影像进行有监督的分类！里面包含完整的算法及TM图像，下载即可进行调试!(K means algorithm using 7 bands of TM remote sensing image supervised classification! Which contains the complete algorithm and the TM image, download it for debugging!)

Spectrum Sensing in Cognitive Radio Approach in Matlab

说明：  matlab中一些重要的课件和资料，比较有用啊！(matlab courseware and some important information, more useful ah!)

HHT的基本理论(黄先生的原文) 小波板换希尔伯特黄变换；理算小波变换原文(Signal filtering, Wavelet transform, Hilbert-Huang transform DWT (Discrete Wavelet Transform) och HHT(Hilbert-Huang Transform).)

图和网络最短路径法则的弗洛伊德算法，从振动论坛下载。挺不错的哟。。(Network map and the law of the shortest path algorithm Freud, from the vibration of the forum to download. Pretty good yo. .)

matlab lms code whaich is used for echo cancellation

卡尔曼程序,用matlab实现,很有用的(Kalman procedures, using matlab to achieve, very useful)