KPCA

MATLAB是一套功能十分强大的工程计算及数据分析软件,具有友好的可视化编程界面及接近数学表达式的自然化语言。针对信号与系统中傅里叶变换具有抽象度高、难于理解的特点，利用MATLAB强大的信号处理功能、阶跃响应，微分方程，卷积定理的内容，通过MATLAB 程序实现。本文介绍了MATLAB在信号与系统仿真中的应用,该软件在通信电子类课程中应用越来越广泛,通过几个典型实例来重点研究。 关键词：MATLAB；阶跃响应；微分方程；卷积；信号与系统；仿真 (MATLAB is a very powerful engineering calculations and data analysis software, with a friendly interface and visual programming language close to naturalizing mathematical expressions. For the Fourier transform of signals and systems with a high degree of abstraction, it is difficult to understand the characteristics, the use of the powerful MATLAB signal processing functions, step response, convolution theorem content differential equations by MATLAB program. This article describes the application of MATLAB in signal and system simulation, the software in the electronic communications courses in applied more widely, by focusing on a few typical examples. Keywords: MATLAB step response signals and systems convolution differential equation simulation )

经验模态分解（Empirical Mode Decomposition,EMD）法是美国国家宇航局美籍华人黄锷（N. E. Huang）等人于1998年创造性地提出的一种新型自适应信号时频处理方法，特别适用于非线性非平稳信号的分析处理。(Empirical Mode Decomposition (Empirical Mode Decomposition, EMD) method is a new kind of video processing method adaptive signal NASA Chinese-American yellow E (NE Huang), who in 1998 proposed a creative way, especially for non- Linear analysis and processing non-stationary signals.)

基于RSSI的质心算法，其中可以实现目标的定位。有用者请下载。(Based on RSSI centroid algorithm, which can achieve the target localization. Useful, please download.)

后处理程序，主要是绘制单向拉伸杆中沿横截面的应力分布图(failed to translate)

偏微分方程反问题的正则化方法，后验参数估计的方法(inverse problems of parabolic equations )

this is the example for matlab GUI

susan 开发源代码 在matlab 中的应用(susan code matlab)

FK和GF算法的matlab实现，并通过随机数对算法进行对比测试(FK and GF algorithm matlab implementation, and through the random number algorithm comparison test)

Code to compute superpixels.

Phase-based Opic Flow Algorithm, described in Gautama, T. and Van Hulle, M.M. [2002]. A Phase-based Approach to the Estimation of the Optical Flow Field Using Spatial Filtering. IEEE Trans. Neural Networks, 13[5], 1127--1136.