How-to-define-a-function-in-MATLAB

精通MATLAB 6.5版北京航空航天大学出版社(Proficient in MATLAB 6.5 version of Beijing University of Aeronautics and Astronautics Press)

关于合成孔径雷达信号的基础知识和如何进行线性调频脉冲信号的压缩及其matlab源码。(Synthetic aperture radar signal on the basis of knowledge and how to carry out a linear FM pulse compression and the matlab source code.)

System will automatically delete the directory

数字水印的嵌入和水印的提取matlab程序(Digital watermark embedding and watermark extraction matlab program)

eemd的源码,内含5个m文件，分别求取不同参数(the source code of eemd the source code of eemd the source code of eemd the source code of eemd...the source code of eemd)

processing the signal which is chirp

It contains the matlab simulation for the Grid connected fuel cell

该程序可用matlab实现三种滤波：切比雪夫1,切比雪夫2和巴特沃斯滤波。可实现信号的滤波预处理。(The program can be used to achieve three filtering matlab: Chebyshev 1, Chebyshev 2 and Butterworth filter. The filter can be realized signal preconditioning.)

维纳滤波器实现中值滤波，该程序是用matlab源代码来实现的。(Wiener filter realization of median filtering, the program source code with matlab achieved.)

独立成分分析（Independent Component Analysis, ICA）是近年来发展起来的一种有效的盲分离技术，最早是由法国学者Herault和Jutten于1986年提出。ICA方法的提出最初是用来解决“鸡尾酒会”问题，其过程可以归纳为，在源信号与传输通道参数均未知的情况下，仅根据源信号的统计特性，出现测信号恢复出源信号。ICA分析的关键在于根据一定的优化准则建立描述输出信号独立程度的优化判据，即目标函数，并设计相应的优化算法，寻求最优的分离矩阵，使得输出信号中各分量尽可能相互独立。采用ICA方法对信号进行盲分离时，可避免过多地受大能量噪声成分的影响，将部分小能量信号源识别出来。随着ICA技术的不断发展，目前ICA技术已经广泛应用于语音增强、音频识别、通信、医学信号处理、金融数据挖掘、图像消噪、数字水印、遥感等领域，并取得了一定的研究成果。(Independent Component Analysis (ICA) Component ini order, developed in recent years is a kind of effective separation technology, originally from French scholars Herault and Jutten in 1986. The proposed method is initially ICA to solve the "cocktail" problem, the process can be divided into, in the source signal transmission channels and in the case of unknown parameters according to the source of the signals, and the statistical characteristics of recovering the source signal. According to the analysis of the ICA key lies in the establishment of optimal criteria described the output signal of the independent, objective function optimization criterion, and the corresponding optimization algorithm, the optimum )