VectorControlSVPWMencoderless

采用信号包络和差分方式进行信号模式识别，可对QPSK，BPSK，AM，FM方式识别(The use of signal envelope and differential mode signal pattern recognition, can QPSK, BPSK, AM, FM identified)

求Weighted/Non-weighted贝叶斯k近邻模型的matlab程序，内含具体说明。(seeking Weighted/Non-weighted k neighbors Bayesian model matla b procedures, containing details.)

高通滤波器的matlab实现具体源代码，数字图像处理处理中最常用的高频提取方法。(High-pass filter matlab source code to achieve specific, processing of digital image processing to extract the most commonly used method of high frequency.)

机器学习中的垃圾邮件分类程序，用matlab做的。从以下链接下载垃圾邮件数据（spam data）：(数据已下载，放在spambase.zip) http://www-stat.stanford.edu/~tibs/ElemStatLearn/index.html 该数据包含57个邮件信息相关的变量，每条邮件可以被分类为垃圾邮件（Y=1）和非垃圾邮件（Y=0）。输出Y的值在文件中每一列的末尾。练习的目标是要预测电子邮件是否为垃圾邮件。 (Machine Learning spam classification procedures, using matlab to do. Data (spam data) from the following link to download the junk mail: (data has been downloaded, put spambase.zip) http://www-stat.stanford.edu/ ~ tibs/ElemStatLearn/index.html The data includes 57 e-mail messages related variables, each message can be classified as spam (Y = 1) and non-spam (Y = 0). Y value of the output end of each column in the file. The goal is to predict exercise email is spam.)

kalman滤波程序，里面包含kalman的讲解及程序实现，对初学者比较有帮助。(a program of kalman )

数值分析-----利用复化的Simpon公式求解圆周率Pi (----- Numerical analysis of Simpon using complex formulas to solve Pi Pi)

matlab engineer solution

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )

matlab通信仿真及应用实例详解,讲解matlab在通信仿真中的应用,很好的资料.(Communication and application of MATLAB simulation examples of detailed,on matlab simulation in communications applications,very good information)

matlab simulation for TL and cable