小波分析与应用（基于MATLAB代码）

一本在Matlab开发环境下，讲解面向对象的编程书籍。适合从事Matlab编程的朋友们。(a book that is suitable for the friends who want to research object oriented programming using Matlab.)

matlab作图程序总汇，相当的好，包含matlab 源程序与课件(matlab plot summary procedure, rather good, and courseware that contains the source code matlab)

Torque equation for human motion

通信中的采样钟恢复，用gardner 算法提取时钟误差。(STR for sampling Time recovery)

一种拉普拉斯算子实现数字图像边缘检测

在matlab环境中自动识别连通区域的大小,最终的权值矩阵就是滤波器的系数，采用波束成形技术的BER计算，包括主成分分析、因子分析、贝叶斯分析，GSM中GMSK调制信号的产生，数学方法是部分子空间法。

Split Bregman TV denoising using compression and decompresion technique

各种方法的去噪程序 den1.m 使用半软阈值方法对图像进行去噪 den1_5_1.m 半软阈值的改进方法 对第一层重构图像进行均值滤波 den1_9.m 半软阈值的改进方法 将线性衰减的函数改为指数的 den1_10.m 半软阈值的改进方法 对第一层的重构图像再次进行小波阈值去噪 den2.m 用软硬阈值函数的改进方法进行去噪 den3.m 用广义阈值函数进行去噪 den4.m 用自适应特征阈值函数进行去噪 wdenoise.m 用Donoho阈值或Birge-Massart策略及软阈值或硬阈值函数进行去噪 meanfilter.m 均值滤波方法进行去噪(对比用) medfilter.m 中值滤波方法进行去噪(对比用)(Denoising procedures for various methods Den1.m using semi soft threshold method for image denoising The improved method of den1_5_1.m semi soft threshold for the first layer of the reconstructed image The improved method of den1_9.m semi soft threshold will be changed linear to exponential. The improved method of den1_10.m semi soft threshold for the first layer of the reconstructed image again for wavelet thresholding denoising Den2.m using the soft and hard threshold function to improve the method of denoising Den3.m using generalized threshold function for denoising Den4.m with adaptive feature threshold function for denoising Wdenoise.m with Donoho threshold or Birge-Massart strategy and soft threshold or hard threshold function for denoising Meanfilter.m mean filtering method for denoising (contrast) Medfilter.m median filtering method for denoising (contrast))

FAST ICA 算法用于ICA实验，可用于人脸识别等领域(FAST ICA algorithm for ICA experiments, can be used in areas such as face recognition)

说明：  2006标准PSO程序，可以用于系统的优化，请大家式一式。有什么好的意见提出来，(2006 standard procedure can be used for system optimization, please-a type. What good ideas put forward, thank you)