MTIfilliter

文化量子粒子群算法，不好找的算法啊！便已顺利通过啊(algorithm procedure for cultural QPSO)

基于有限元法求解二维边值问题的matlab程序(Based on the finite element method of two-dimensional boundary value problem matlab program)

NICAM（丽音）系统编解码Matlab源程序(NICAM encoder and decoder)

程序功能为谱聚类实现系统的分区。给出的是39节点的标准的ieee算例。可以运行，有图形显示。(The program will function as spectral clustering system partition. Given 39-node standard IEEE example. Can run graphical display.)

fft与ifft系列程序，用于图像的滤波算法，信息提取。使用matlab环境，易用性强。 (fft and ifft program, matlab environment, easy to use.)

matlab examples.Viewing the magnitude response of ideal and practical lowpass filters

Dynamic Time Warping Function in MATLAB

这是一份MATLAB基础课件，由于我也是初学者，这部课件讲的很浅显，但比较适合初学者对MATLAB所有功能的一个初步了解内容包括涵数值数组及其运算， M文件和面向对象编成， 字符串数组， 符号变量， matlab 绘图 及 Simulnk动态仿真。以及两个基本浅显的程序题。此为第 1章。(This is a basic MATLAB courseware, because I am also a beginner, this software is very simple-speaking, but more suitable for beginners of all the features of MATLAB, a preliminary understanding of the content including the Han and its numerical array computing, M documents and for object into string array, variable symbols, matlab graphics and dynamic simulation Simulnk. As well as the two basic procedures for simple questions. This is Chapter 1.)

并联有源共模电流抑制方法的matlab仿真，建立仿真模型，分析补偿特性(common mode current inhibition of Matlab simulation, simulation model building, analyzing characteristics compensation)

This file compares three different versions of the Kalman filter. The Kalman filter is used for recursive parameter estimation. The Kalman filter can handle noisy measurements. The first implemented filter (fcn_KF) is the Kalman filter with standard update of the covariance matrix P. The covariance matrix reflects the uncertainties of the predictions. To improve the numerical stability Potter developed a square root update (fcn_KF_SRP) of the covariance matrix P. Another version is the square root covariance update via triangularization (fcn_KF_SRT). This file generates a model. Then the three Kalman filters perform an estimation of the model parameter. At the end the results are compared. Sources: Simon, D. (2006): Optimal state estimation Kaminski, P. (1971): Discrete Square Root Filtering: A Survey of Current Techniques Golub, G. (1996): Matrix Computations