hmmgenerate

这个一个很全面的数字信号处理的实验工具包，里面包含了大部分的数字信号处理实验的各个方面。希望对大家有帮助。(This a very comprehensive test of digital signal processing tool kit, which contains most of the digital signal processing aspects of the experiment. Hope to help.)

基于整数小波变换的图像无损压缩方法(Based on Integer Wavelet Transform image lossless compression method)

包含大量遗传算法程序，还有部分PID参数优化函数，希望对朋友们有用。(Contains a large amount of genetic algorithm procedure, part of PID parameter optimization function, in the hope that useful friends.)

This is matlab code for simulation pdf of Nakagami

samsung smart tv app

语音增强 提供io接口及处理的工具箱等，语音增强效果比较好(Speech enhancement provide the IO interface and the processing toolbox, and so on, the speech enhancement effect is better)

This paper presents a new and efficient approach for capacitor placement in radial distribution systems (RDS) that determine the optimal locations and size of capacitor with an objective of improving the voltage profile and reduction of power loss. The solution methodology has two parts: in part one the loss sensitivity factors (LSF) are used to select the candidate locations for the capacitor placement and in part two a new algorithm that employs Dijkstra Algorithm (DA) is used to estimate the optimal size of capacitors at the optimal buses determined in part one. The main advantage of the proposed method is that it does not require any external control parameters. The other advantage is that it handles the objective function and the constraints separately. The proposed method is applied to 33 & 69 RDS. The solutions obtained by the proposed method are compared with other methods. The proposed method has outperformed the other methods in terms of the quality of solution. OPTIMAL C

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

蚁群算法实现tsp问题的解，适合初学者使用(Ant colony optimization tsp solution of the problem, for beginners)

this file gives an overall concept for dsss