version_1_2_070520

GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Expectation-Maximization (EM) iterative learning algorithms. By using this model, Gaussian Mixture Regression (GMR) can then be used to retrieve partial output data by specifying the desired inputs. It then acts as a generalization process that computes conditional probability with respect to partially observed data.

pid 控制优化 基于混乱粒子的参数优化(pid control optimization)

this code for image segmentation

采用时频分布参数来描述语音特征，对基于正弦模型的多种时频参数进行了比较(Time-frequency distribution parameters used to describe the voice characteristics of the multiple sinusoidal model-based time-frequency parameters are compared)

利用logGabor函数分别提取待匹配图和模板图的相位信息作为匹配基元，进行互相关运算，寻找最佳匹配位置(Use to be extracted separately logGabor function map and template matching of the phase diagram as an information matching primitives to carry out cross-correlation calculation, find the best match position)

High Speed Face Recognition Based on Discrete Cosine Transforms and Neural Networks

说明：  用matlab编写的采用遗传算法进行图像分割的一个程序(using Matlab prepared using genetic algorithms for image segmentation of a program)

最优化算法DFP算法源代码 可以实现求极小值的(dfp program orginal file)

应用matlab 分析机械力学中的工程振动问题,实例2。(Matlab applications in the engineering mechanics analysis of vibration problems, Example 2.)

用matlab编写的牛顿迭代方法求解非线性方程组：数值分析中很经典的代码(a matlab code of newton method solve system of nonlinear equations)