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这里面的代码是2DPCA的。这篇文章发表在PAMI上,Two-Dimensional PCA: A New Approach to Appearance-Based Face Representation and Recognition.google搜索已经引用681次。这里的代码是原作者的。这个分类不太好，语音识别是最近的，这是模式识别里的经典算法。(matlab code of 2DPCA)

语音信号时频分析，包括语谱图，过零率，自编的自相关，以及最后用了三种方法（短时能量和过零率、谱熵法、Teager算子）进行端点检测，代码完整且测试通过(time and frequency domain analysis of speech signals,including spectrogram,rate of zerocrossing,autocorrelation.and three method of endpoint detection,especially the Teager )

一个谱相减程序（IN MATLAB）， 一个谱相减程序（IN MATLAB），(a spectral subtraction procedure (IN MATLAB), a spectral subtraction procedure (IN MATLAB).)

C# 对接 Java 3des md5WithRsa, 有需要的可以参考下(If you need C # to dock Java 3des md5WithRsa, you can refer to the following)

性别识别系统的Matlab实现，比较简单容易理解(Gender Recognition System Matlab implementation, relatively simple easy to understand)

基于熵的端点检测算法，比传统的端点检测能更精确的检测出端点(endpoint detection algorithm than the traditional endpoint detection more accurate detection of Endpoint)

基于FastICA相结合实现的语音信号的采集、随机混合，再通过盲分离将混合后的语音信号分离(Speech signal acquisition and random mixing based on FastICA, and then the mixed speech signal is separated by blind separation.)

用自相关函数提取语音信号基频，提取音频文件的基频等高线(Use the autocorrelation function on segments of the signal (windowsize: 100ms) and compute the fundamental frequency. Use a max_time_lag of 100ms in the autocorrelation function and a window shift of 25ms. Create a fundamental frequency vector and plot the pitch contour.)

基于matlab环境下的一个独立分量分析的小程序，包括对三个语音信号混合后的ica分析(Analysis program based on an independent component in the Matlab environment, including analysis of three speech signals mixed after ica)

多信号分离MUSIC的经典学习程序 对初学者帮助很大(it is a baisc and useful code of the multiple signal classfication for the beginners.)