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离散时间语音信号处理--原理与应用 相关matlab文件(Discrete-Time Speech Signal Processing:Principles and Practice )

k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。(k-means algorithm accepts input k then n data objects into k clusters in order to make clustering satisfy obtained: the objects in the same cluster high similarity different clustering object similarity small. Cluster similarity is the use of the mean of each cluster of objects that get a " central object" (center of gravity) to perform the calculation.)

Pattern classification claasificiation of sample with matlab code

power system tool box

Segmentation by growing a region from seed point using intensity mean measure.Simple but effective example of "Region Growing" from a single seed point.

说明：  基于鱼眼效果的产生图像，里面是比较简单的原理代码，方格图成像(Fish eye effect on the production images, which is a relatively simple principle of the code, grid map imaging)

mfiles useful for finding huffman code

implementation of butterworth high pass filter

It is possible to confirm whether error of Automatic Phase Synchronization excess the setting value of parameter No.13437-No.13440 (Threshold for Automatic Phase Synchronization error detection signal) by this signal. The signals turn to 1 in the following case: • Error of Automatic Phase Synchronization excess threshold. The signals turn to 0 in the following cases: • Error of Automatic Phase Synchronization does not excess threshold.

能够把输入信号分解为多个IMF分量，并进行Hilbert变换，求得信号的时频分布谱图。(Be able to input signal is decomposed into several IMF components and carry out Hilbert transform, time-frequency distribution obtained spectrum.)