Lecture_19_MATLAB_ScriptaFunctionFiles06

说明：  张贤达《现代信号处理（第二版）》习题与解答(Xian-up &quot Modern Signal Processing (Second Edition)&quot problem sets and answers)

Matlab和C的混编，用于SAR图像去相干斑，将处理加性噪声的BM3D推广到SAR。(Functions for Matlab for the denoising of a SAR image corrupted by multiplicative speckle noise with the technique described in "A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage", written by S. Parrilli, M. Poderico, C.V. Angelino and L. Verdoliva)

MATLAB描点，数据量有一万多。把一万多个点描到图上。真的有以往多个点，数据量很大了吧。(MATLAB describe points, more than 10,000 of the amount of data. More than 10,000 pointillism to the map. Really have more points in the past, large amounts of data it.)

This program proveides a solution by Ghassan Hamarneh for detection curves using ACTIVE CONTOUR MODELS

经验模态分解，matlab实现，用于信号的降噪处理，提取特征值处理等经验模态分解，这是用汉语注释的EMD程序，很不错的。％ 语法 ％ IMF = EMD(X) ％ IMF = EMD(X,..., Option_name ,Option_value,...) ％ IMF = EMD(X,OPTS) ％ [IMF,ORT,NB_ITERATIONS] = EMD(...) (This is annotated in Chinese EMD procedures, very good. Syntax IMF = EMD (X) IMF = EMD (X ,..., Option_name, Option_value ,...) IMF = EMD (X, OPTS) [IMF, ORT, NB_ITERATIONS] = EMD (.. .(Empirical mode decomposition, matlab, used in signal noise reduction processing, extraction of characteristic value processing, etc)

说明：  clpso,pso的改进版本，又名学习策略pso(clpso, pso improved version, also known as learning strategies pso)

说明：  萨丹哈圣诞节警方货到付款·空间fks富士康的粉红色的发挥skf和·(How many local charge on the identity of happened)

语音识别中的模型和算法：动态时间归正技术（DTW），隐马尔可夫模型（HMM），高斯混合模型（GMM），高斯混合模型（GMM）(Speech Recognition model and algorithms : dynamic time Reformed technology (DTW) Hidden Markov Model (HMM), Gaussian mixture model (GMM), Gaussian mixture model (GMM))

高丝混合模型，内涵matlab程序，用EM算法(Kose hybrid model, the connotation matlab program, using the EM algorithm)

GNU Octave A high-level interactive language for numerical computations Edition 3 for Octave version 3.0.0 July 2007 (GNU Octave A high-level interactive language for numerical computations Edition 3 for Octave version 3.0.0 July 2007)