geometric-factor

Find peaks in signal. Look for local maxima and minima. In the window of search find the maximum maxima and the minimum minuma. Return two values which are the maximum and the minimum local maximas

Auto-correlation and cross-correlation of a period signal

说明：  用matlab来实现对图像进行直方图处理的源程序。(Using matlab to achieve the image histogram processing of the source.)

均衡技术的matlab仿真。包括时域均衡和频域均衡后的信噪比对比(Equalization matlab simulation. Including time domain equalization and frequency domain equalization SNR comparison)

样本熵的matlab源代码，可以求出样本的熵值(Sample Entropy)

基于matlab的ASK,PSK例程，比较适合初学者使用实现相关功能。信号调制。(signal modulation)

老外编的标准pso算法的matlab工具箱，该工具箱将PSO算法的核心部分封装起来，提供给用户的为算法的可调参数，用户只需要定义好自己需要优化的函数(计算最小值或者最大值)，并设置好函数自变量的取值范围、每步迭代允许的最大变化量(称为最大速度，Max_V)等，即可自行优化。(Part of the standard of foreigners pso algorithm matlab toolbox, the toolbox will be the core of the PSO algorithm package together to provide to the user adjustable parameters for the algorithm, users only need to define their own needs better optimization function (calculation of minimum or maximum value), and set a good function, since the range of variables, each iteration step the maximum allowable variation (known as the maximum speed, Max_V) and so on, can be self-optimizing.)

此段代买可以用来实现层次分析法，通过输入参数、更改参数，利用循环自动检验是否符合层次分析法的要求(solve the AHP problem)

基于SVM的人脸识别系统，matlab实现，google code 最新代码。(face recgonition based on SVM,impleted on Matlab .The code is downloaded from google this days.)

本实验语音库为免费的柏林情感语音库，其采样频率为16KHZ，16bit量化。该语音库共有500 句情感语音信号，分别由十名专业演员(5 男，5 女)在不同情感状态下（高兴、愤怒、平静、悲伤、害怕、厌烦、憎恨）朗读十句不同文本的德语组成。本实验选取其中的部分情感（高兴、愤怒、悲伤）加以识别。仿真实验环境为MATLAB7.0。 实验选取的情感特征为短时平均能量、短时平均幅度、基频和短时过零率。为了降低不同人在表达不同情感时的个人差异造成的影响，本文实验过程中将提取的情感特征进行归一化处理。归一化采取将同一个人的三种情感语音信号的情感特征放在一起归一化处理，并将归一化后的情感特征作为KNN分类器的训练样本和测试样本。 该实验使用了传统的KNN算法和改进算法两种识别方式，通过实验结果对比了各自的特点。 (This experiment YuYinKu for free Berlin YuYinKu emotion, the sampling frequency for 16 KHZ, 16 bit quantification. The YuYinKu 500 words of emotional speech signal, respectively by ten professional actors (5 male, five female) in different emotional state (happy, anger, sadness, fear, calm, bored, hate) read ten sentences in different text of the German. This experiment selection of part of the emotions (joy, anger, sadness) is recognized. The simulation experiment environment for MATLAB7.0. The selection of emotional characteristics for short-term average energy, short-term average amplitude, frequency, and the short zero rate. In order to reduce the different people in different emotional expression of the impact of individual differences, the experiment process will extract emotional characteristics is normalized. The normalized will take the same three kind of emotional speech signal emotional features normalized put together, and after the normalized the emotional characteristics)