significance

随机场的模拟（利用解析解模拟参数的随机场，markov自相关函数）(analytical simulation of random field)

按照A*算法的步骤来实现。Matlab code(According to the steps of the A* algorithm to achieve)

本模块对车用动力锂电池的三种主要等效电路模型进行建模和仿真，搭建了相应的仿真模块。(In this module, three main equivalent circuit models of vehicle power lithium battery are modeled and simulated, and the corresponding simulation module is built.)

使用matlab的m语言开发，功能为rake接收机的链路生成。其中包含短码生成成，业务信道长码生成，瑞利衰落信道代码， 哈达码变换，用户原始数据扩频和信道衰落 (Use Matlab m-language development, functional link generated for the rake receiver. Contains short code generated into business channel long code generation, code Rayleigh fading channels, Hadamard transform raw data of users spread spectrum and channel fading)

医学信号处理 设计目的：通过学习心电信号的知识和小波方法，结合学过的医学信号处理理论，实现心电QRS波形检测算法。(Medical signal processing design Objective: Through the study of ECG knowledge and wavelet method, combined with studies of medical signal processing theory, realize QRS ECG waveform detection algorithm.)

利用混合巡游方法控制时空混沌1000-2618(2013)05-0475-05(Control of spatiotemporal chaos by a hybrid itinerant feedback method)

％ EM algorithm for k multidimensional Gaussian mixture estimation ％ ％ Inputs: ％ X(n,d) - input data, n=number of observations, d=dimension of variable ％ k - maximum number of Gaussian components allowed ％ ltol - percentage of the log likelihood difference between 2 iterations ([] for none) ％ maxiter - maximum number of iteration allowed ([] for none) ％ pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) ％ Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) ％ ％ Ouputs: ％ W(1,k) - estimated weights of GM ％ M(d,k) - estimated mean vectors of GM ％ V(d,d,k) - estimated covariance matrices of GM ％ L - log likelihood of estimates ％( EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates)

MATLAB潮流计算(MATLAB flow calculation)

particle swarm optimization codes

一种改进的卡尔曼滤波算法，用于多传感器数据融合(An improved Kalman filtering algorithm for multi-sensor data fusion)