dijstra

读取语音信号（用matlab的wavread指令），把语音信号分帧、加窗，进行清浊分割，提取基 频，这一部分较简单，自己编程序做。参考文献自己到图书馆期刊网上查找。 提取语音信号的lpc参数，可调用lpcfit.m 程序（我提供，见附件），将源、目标语音的浊音 段的lpc系数进行DTW规整，调用pathita2.m 程序（我提供，见附件）。将规整得到的lpc系数 转换成lsp参数，调用lpcar2ls.m 程序（我提供，见附件）， 再进行转换映射，调用matlab 的指令newrbe。(read the speech signal (using Matlab wavread Directive), Voice Signal frames, Windowed, Qingzhuo segmentation, extracting fundamental frequency, this part is relatively simple, they programmed to do. References their online journals to the library search. Voice Signal Extraction lpc parameters can be called lpcfit.m (I provide, see Annex), the source, Voiced objective voice of the lpc coefficient DTW structured, Call pathita2.m (I provide, see Annex). Structured to the lpc lsp conversion coefficient parameters, calling lpcar2ls.m (I offer see Annex), the shift mapping, called the directive newrbe Matlab.)

文件中包含matlab中常用的分类方法 以及归一化代码 供自学(The file contains the classification methods commonly used in MATLAB and the normalized code for self-study)

ARIMA模型，用来对非平稳信号的功率谱估计，很有用！(ARIMA model, used for non-stationary signals in power spectrum estimation, very useful!)

阿兰方差的基本实现，可对滤波效果进行检验。(Allan scheme,which can terify the results of denoising in terms of three noise factors.)

说明：  用于各种潮流计算和最有潮流计算的matpower 中文手册(For various flow calculation and the most current computing matpower Chinese manual)

基于YUV格式的视频做的数字视频水印，该算法可到达很好的健壮性和透明性(YUV format video, digital video watermark, the algorithm can reach a good robustness and transparency)

matlab m文件 EM算法混合高斯模型(matlab m file EM algorithm Gaussian mixture model)

利用分数阶傅立叶变换进行信号参数估计，本程序是对LFM信号的参数中心频率和调频斜率进行估计(Use FRFT signal parameter estimation, the parameters of this program is the center frequency and frequency rate LFM signal is estimated)

这个是一个排序熵的程序，它能够达到信息熵的目的，算是一个改进的方法。应用起来比较方便(This program is a sort of entropy, it can achieve the purpose of information entropy can be regarded as an improved method. Was easier to apply)

Implementation of symbol by symbol detection, sequence detection, and Viterbi algorithm in channel with ISI and compare performance based on SNR, channel taps, and packet size.