openslam6

tools for processing crypto in matlab written inc c++ ebook for

对于小波去噪，采用的是小波函数，并在去噪同时进行语音的压缩。(for wavelet denoising, using the wavelet denoising and simultaneously voice compression.)

说明：  AF的性能仿真即误码率理论值的数值仿真分析(AF BER performance simulation is the theoretical value of the numerical simulation)

多目标跟踪，PHD滤波器的使用，实现过程采用高斯混合方法(Multi-target tracking, using PHD filter realization method using Gaussian mixture)

基于主成分分析的人脸识别，应用K-L变换作特征处理(Face recognition based PCA)

基于HRRP的Prony算法，可用于实现目标散射中心个数的估计及识别(Based on the HRRP the Prony algorithm, can be used to achieve a number of estimates and identification of target scattering centers)

MATLAB实现的KNN 压缩文件包含m文件和wine.txt(机器学习著名的红酒数据集，下载自UCI大学机器学习数据集： http://archive.ics.uci.edu/ml/datasets/Wine） (knn wrote in MATLAB)

K最邻近密度估计技术是一种分类方法，不是聚类方法。 不是最优方法，实践中比较流行。 通俗但不一定易懂的规则是： 1.计算待分类数据和不同类中每一个数据的距离（欧氏或马氏）。 2.选出最小的前K数据个距离，这里用到选择排序法。 3.对比这前K个距离，找出K个数据中包含最多的是那个类的数据，即为待分类数据所在的类。(K nearest neighbor density estimation is a classification method, not a clustering method. It is not the best method, but it is popular in practice. Popular but not necessarily understandable rule is: 1. calculate the distance between the data to be classified and the data in each other (Euclidean or Markov). 2. select the minimum distance from the previous K data, where the choice sorting method is used. 3. compare the previous K distances to find out which K data contains the most data of that class, that is, the class to which the data to be classified is located.)

This function plot a series of rects described from the N columns of a matrix 4xN, eaach column is of the form [x,y,w,h]

说明：  matlab程序设计基础ppt 函数文件程序设计的基本结构(matlab program design based on function ppt document the basic structure of program design)