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求两个时间序列的相关系数，KL散度。可以比较时间序列之间的相关性(KL divergence && correlation coefficent)

Training software for Markov Random Fields used at INRA

Implementation of the Murty algorithm to obtain the best K assignments. Includes the implementation of the Jonker-Volgenant algorithm. Usual applications are multiple target tracking algorithms, Joint Probabilistic Data Association (JPDA), Multiple Hypothesis Tracking (MHT), Global Nearest Neighbours (GNN), etc. Based on the original code by Jonker-Volgenant, and the Murty Matlab implementation by Eric Trautmann Can be used both from Java or Matlab. Time for a 100x100 assignment problem, with k=20: • Matlab implementation: 54.5 sec • Java implementation: 1 sec

利用matlab仿真GPS坐标转换，即知道一点的GPS坐标利用测出来的距离俯仰方位信息计算另外一点的GPS坐标。(GPS coordinates conversion using matlab simulation, that is to know that the GPS coordinates use the distance measured from the pitching position information to calculate the GPS coordinates of another point.)

Root finding using Secant method

语音分帧程序，对一个语音信号进行分帧，并研究分帧后的短时能量和过零率特性(Voice framing procedures, a voice signal framing, and to study the sub-frame after the short-term energy and zero crossing rate characteristics)

This helps for writing Particle swarm optimization code

时频工具箱，以上给了很多函数，但常用的基本就是短时傅里叶变换STFT、Wigner-Ville分布WVD、伪Wigner-Ville分布PWVD和提取瘠ridges、得到理想时频表示tfrideal。(Time-frequency toolbox over to a lot of functions, but the basic is commonly used short-time Fourier transform STFT, Wigner-Ville distribution WVD, pseudo-Wigner-Ville distribution PWVD and extraction barren ridges, when you get the ideal frequency representation tfrideal.)

Low density parity check matrix(Description A program written for generating LDPC matrix in the as pattern as discussed in the research paper , " Time varying periodic convolutional codes with low density parity check matrix" by Alberto jiménez Felströ m and Kamil Sh. zigangirov IEEE Transaction on information theory vol 45 no 6 sept 1999. pages 2181-2191)

哈弗曼编码用MATLAB语言和C语言来解释(Huffman coding using MATLAB and C language to explain)