lpcc-speech-recognition-master

本程序用于对三维转台目标进行ISAR成像（发射LFM信号，stretch处理）(This program is used for three-dimensional turntable targets ISAR imaging (LFM signal transmitter, stretch processing))

基于全相位频谱分析的相位差频谱校正法.PDF(Phase Difference Correcting Spectrum Method Based on All-phase Spectrum Analysis)

单机并行遗传算的一个程序 简单易用 在单机运行 性能稍差(Stand-alone parallel genetic operators of a program easy to use stand-alone operating performance somewhat less)

对fastica工具箱进行了简化和程序的提取，增加了详细的注释。采用fastica算法的matlab程序，用以进行胎儿心电信号的提取。包含数据和程序，希望有用！！(Fastica toolbox to simplify and procedures of extraction, the detailed notes. Matlab program with fastica algorithms for the extraction of fetal ECG. Contains data and programs seek to help!!)

计算地球物理中重力梯度的数值 给出相应可改变模型的代码(The calculation of the gravity gradient in Geophysics Give the code for the corresponding change model)

useful matlab codes for beginners

Golden Search mfile in matlab

信号经过两个独立的信道传输，两个信道的信道复增益分别为 和 。 是独立同分布的复高斯随机变量，实部虚部独立、均值为0，实部虚部的方差都是1。采用某分集技术后输出的信噪比为 ，其中 是常数， 是在 之间均匀分布的随机变量。请就不同的 、 ，用仿真的方法画出 的累积分布函数。(signal after two independent Channel Tunnel, Channel 2 Channel Minute respectively, and gain. Independence is the same complex Gaussian distribution of random variables, is the imaginary part of the Department of independence, mean 0 and the real part of the imaginary part is a variance. Using a diversity of the output signal-to-noise, which is constant, is the uniform distribution between random variables. Please different, and simulation methods paint the cumulative distribution function.)

k均值的分析与，图解，自己亲自测试，能用并且(k-mean analysis, diagrams, personally testing, use )

　K-means算法是最为经典的基于划分的聚类方法，是十大经典数据挖掘算法之一。K-means算法的基本思想是：以空间中k个点为中心进行聚类，对最靠近他们的对象归类。通过迭代的方法，逐次更新各聚类中心的值，直至得到最好的聚类结果。(K-means algorithm is based on the division of the classic clustering method, is ten classic one of data mining algorithm. K-means the basic idea of the algorithm is: to the space K point as the center of the cluster analysis, near their object classification. Through the iterative method, each successive update clustering center value, until get the best clustering results. )