Timing_Symcronization

读入一幅256*256图像，将它分成8*8pixel的若干块，对每块做DCT变换，保留Z型顺序的若干变换系数，进行IDCT重构图像，计算重构图像的信噪比(Reading a 256* 256 image, it will be divided into several blocks of 8*8 pixel, keep each optimal Z transformation of sequence number, IDCT transform coefficient calculation reconstruction image reconstruction images,and the signal-to-noise ratio)

本实例主要是MATLAB搭建的spwm模块 通过仿真 我们可以很清晰的看到该模块能将输入的正弦波和固定频率的三角载波进行比较 输出spwm波 结构简单 易于理解(this model mainly about the spwm generation.we can clearly see the spwm wave from the output and drive the IGBT.)

对数据集特征压缩，用样本熵的方法进行压缩，简单，易懂，matlab程序源代码(Compressed data set characteristics, sample entropy compression, simple, understandable, matlab program source code)

fuzzy controller design for inverted pendulum

DEE model is use to define the model

This function is for optimization by strong wolfe condition

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. )

Non coherent GPS signal acquistion file in MATLAB

matlab之语音处理与合成工具箱的随书程序！！！Good!!!It s useful for you !!!(Good!!!It s useful for you !!!)

设定ARMA模型参数,求所采集到的数据的双谱和特征量（带有测试数据）(Autoagressive Moving Average)