一个好用的稀疏压缩感知算法程序

PCM的编码与解码基于matlab的环境实现方法，只需要改变输入信源即可实现编码与解码; PCM的编码与解码基于matlab的环境实现方法，只需要改变输入信源即可实现编码与解码; PCM的编码与解码基于matlab的环境实现方法，只需要改变输入信源即可实现编码与解码;

这也是关系k紧邻的程序，希望对大家有帮助(This is also a close relationship between the k of the procedure, we hope to help)

粒子群寻优，根据现场数据寻找合适的模型参数，为了后续控制(Particle swarm optimization, according to the field data to find the appropriate model parameters, for the follow-up control)

对压力传感器的非线性及温度系数进行有效修正，确保修正后精度达到0.05%

说明：  基于已知特性信道的QAM系统的仿真和性能分析(Based on the known characteristics of the QAM channel system simulation and performance analysis)

基于雷达一维距离像的目标识别，采用最大相关系数算法，是最简单的基于HRRP的目标识别算法，适合新手。(Radar HRRP target recognition, the maximum correlation coefficient algorithm is based on the most simple HRRP target recognition algorithms, suitable for the novice.)

有借鉴意义哦，BP神经网络的整个训练过程,空间目标识别，采用PM算法。( There are reference Oh, The entire training process BP neural network, Space target recognition algorithm using PM.)

Algo3-5.c C program for implementing Algorithm 3.5 Algorithm translated to C by: Dr. Norman Fahrer IBM and Macintosh verification by: Daniel Mathews NUMERICAL METHODS: C Programs, (c) John H. Mathews 1995 To accompany the text: NUMERICAL METHODS for Mathematics, Science and Engineering, 2nd Ed, 1992 Prentice Hall, Englewood Cliffs, New Jersey, 07632, U.S.A. Prentice Hall, Inc. USA, Canada, Mexico ISBN 0-13-624990-6 Prentice Hall, International Editions: ISBN 0-13-625047-5 This free software is compliments of the author. E-mail address: in "mathews@fullerton.edu" Algorithm 3.5 (Gauss-Seidel Iteration). Section 3.7, Iterative Methods for Linear Systems, Page 187

经典的张正友的摄像机的两步标定程序，包括单目标定和立体标定程序。代码是基于matlab(Zhengyou Zhang classic two-step camera calibration procedures, including single-target and three-dimensional calibration procedures. Code is based on matlab)

说明：   这是一个用小波神经网络进行非线性函数逼近的例子，拟合效果非常好，保证能运行！有详细注释！我是参考《青岛海洋大学学报》 2001年第1期 一种基于BP算法学习的小波神经网络编写的，大家可以针对原文更好的理解我的程序！(This is a wavelet neural network with nonlinear function approximation example of fitting results is very good, guaranteed to run! Detailed Notes! I refer to Journal of Ocean University of Qingdao，2001 ，“a learning algorithm based on BP wavelet neural network ”, you will understand me better for program!)