emd分解，通过emd分解重构信号实现降噪

用Matlab绘制股市图形范例，含具体步骤说明(draw figure of stock market with Matlab)

此为进行独立成分分析(ICA)的matlab代码，盲源分离(BSS)是指在不知源信号和传输通道的参数的情况下，根据输入源信号的统计特性，仅由观测信号恢复出源信号各个独立成分的过程。这一过程又称为独立成分分析(ICA)。(This is the independent component analysis (ICA) of the matlab code, Blind Source Separation (BSS) is not knowing the source signal and transmission channel parameters, according to the statistical characteristics of the input signal, only the observation signal to restore the source signal The process of each individual component. This process is also known as Independent Component Analysis (ICA).)

Fitcircle matlab code

PCA技术的一大好处是对数据进行降维的处理。我们可以对新求出的“主元”向量的重要性进行排序，根据需要取前面最重要的部分，将后面的维数省去，可以达到降维从而简化模型或是对数据进行压缩的效果。同时最大程度的保持了原有数据的信息。 (A major advantage of PCA technology is reduce the dimension of the data processing. We can calculate the new " principal component" vector order of importance, according to need to take the most important part of the front, eliminating the rear of the dimensions, dimension reduction can be achieved to simplify the model or the effect of data compression . At the same time maintaining the greatest degree of the original data.)

通过Matlab程序，将word文档中词义相近的词语聚类，并分析计算聚类后不同类别词语的频数。(By Matlab procedures, the word document clustering words of similar meaning, and to analyze the frequency of different types of words after computing clusters.)

This matlab code calculates the channel capacity over AWGN channel and the ergodic channel capacity over Rayleigh fading channel.

说明：  基于LMS算法的matlab实现，比较基本的LMS算法，可用于自适应滤波器仿真(Matlab implementation based on LMS algorithm is a basic implementation of LMS algorithm for adaptive filter simulation.)

自己刚学习时练习用的软件，挺好的，如果有初学以尝试下者可(Their practice with just learning the software, very good, if beginners to try the next may)

说明：  计算海洋混合层和障碍层深度并通过M_Map工具包画出全球海洋MLD和BL的分布图(It is quasi homogeneous layer in the upper ocean where variation of density is negligible.)

A matrix of symbolic elements is reasonably useful for many analytic linear algebra applications, and for analytic vector, matrix and tensor differentiation. This function produces a matrix of arbitrary dimension of symbolic elements that are indexed by their position in the symbolic matrix for ease of reference. EXAMPLE >> M = symMat([2 2], m , real ) M = [ m11, m12] [ m21, m22] >> class(M) ans = sym >> det(M) ans = m11*m22 - m12*m21