小波包变换程序matlab

说明：  完整的curvelet变换(2.0)实现(complete curvelet transform (2.0) Implementation)

journal with respect to research work with some related work on routing in networks.

这里包含使用C、matlab等多种语音以多种方式实现LDPC的多种算法。(This includes using C, matlab, and other voice in a variety of ways to achieve a variety of LDPC algorithm.)

比较好的连续潮流算法，结构比较清楚，收敛性能好(Good continuation method)

第7章语音信号的减噪176 7.1自适应滤波器减噪176 7.1.1LMS算法基本原理176 7.1.2基本LMS自适应算法178 7.1.3LMS的自适应陷波器181 7.2谱减法减噪184 7.2.1基本谱减法184 7.2.2改进的谱减法187 7.3维纳滤波法减噪195 7.3.1维纳滤波的基本原理195 7.3.2维纳滤波减噪的具体步骤和函数WienerScalart96197 7.3.3维纳滤波的MATLAB例子199(Noise Chapter 7 of the speech signal noise reduction algorithm for adaptive filters 176 7.1 Fundamentals 7.1.2 Basic LMS adaptive algorithm 176 178 7.1.3LMS of 176 7.1.1LMS adaptive notch filter 181 7.2 184 7.2 spectral subtraction noise reduction 184 7.2.2 .1 basic spectral subtraction improved spectral subtraction method of noise reduction Wiener filter 187 195 7.3 Fundamentals 7.3.1 195 7.3.2 Wiener filtering Wiener filter noise of concrete steps and functions WienerScalart96197 7.3.3-dimensional MATLAB examples Carolina filter 199)

使用matlab模拟高斯在大气中传输，可以观察到一些具体特性参数，可以修改，可以看到束腰的分布和光强的变化

这是一份MATLAB基础课件，由于我也是初学者，这部课件讲的很浅显，但比较适合初学者对MATLAB所有功能的一个初步了解内容包括涵数值数组及其运算， M文件和面向对象编成， 字符串数组， 符号变量， matlab 绘图 及 Simulnk动态仿真。以及两个基本浅显的程序题。此为第 6章。(This is a basic MATLAB courseware, because I am also a beginner, this software is very simple-speaking, but more suitable for beginners of all the features of MATLAB, a preliminary understanding of the content including the Han and its numerical array computing, M documents and for object into string array, variable symbols, matlab graphics and dynamic simulation Simulnk. As well as the two basic procedures for simple questions. This is Chapter 6.)

控制领域：转台伺服控制系统的研究，摩擦力矩，齿槽力矩等(Control areas: Servo Control System, friction torque, cogging torque)

判断下列方阵是否可对角化，是否为正定二次型（顺序主子式判断法、特征值判别法）(using MATLAB to determine if a the matrix is diagonalizable，if the real vector space is definite quadratic)

说明：  ANN-BP分类器设计，用其中一半的数据采用ANN-BP算法设计分类器，另一半数据用于测试分类器性能。(ANN-BP classifier design, with half of the data using ANN-BP algorithm design classifier, the other half of the data used to test the classifier performance.)