Simulated-annealing--particle

matlab6.5图形图像处理源程序 matlab6.5图形图像处理源程序(matlab6.5 Graphics and Image Processing source)

本书系统地介绍MATLAB 7.0的混合编程方法和技巧。本书既适合初学者自学，也适用于高级MATLAB用户，可作为高等数学、计算机、电子工程、数值分析、信息工程等课程的教学参考书，也可供上述领域的科研工作者参考。(This book systematically introduces MATLAB 7.0 mix of programming methods and techniques. This book not only suitable for beginners self-learning, also applies to high-level MATLAB users, can be used as advanced mathematics, computer, electronic engineering, numerical analysis, information engineering curriculum reference books are also available in these areas of research workers.)

说明：  混沌工具箱 C-C方法计算时间延迟和嵌入维数 混沌时间序列预测(Chaos Toolbox CC method to calculate time delay and embedding dimension of chaotic time series prediction)

用matlab实现的RTKfilter实现滤波处理(Achieved with matlab filtering implemented RTKfilter)

该程序可用于近红外光谱二阶求导预处理，经本人实测，程序可用。(The program can be used near-infrared spectroscopy second derivative pretreatment, as I found, the program is available.)

本程序详细区别了matlab中pca、svd、eig三个函数的区别和联系。对于学习pca有极大帮助(This program detailing the differences between the differences and connections in matlab pca, svd, eig three functions. Pca great help for learning)

非常简单的卡尔曼滤波程序，便于大家学习卡尔曼滤波。(Very simple Kalman filtering program, easy to learn the Kalman filter.)

这是用身高体重数据进行性别分类的实验。 用最小错误率贝叶斯分类器决策时，首先通过比较概率大小判断一个体重身高二维向量代表的人是男是女，然后再逐一与已知性别的数据比较，就可以得到错误率的统计。然后改变先验概率，重复上面的过程，观察数据结果的变化。 用最小风险贝叶斯分类器决策时，首先求出用最小错误率贝叶斯分类器得到的条件概率；然后根据人为给定的决策表，根据公式算出条件风险；然后逐一比较条件风险，找出使条件风险最小的决策（也就是分类）。最后用分类得到的结果逐一比较已经知道的原始数据，统计处错误率。 (This is the height and weight data for gender classification experiment. With the minimum error rate Bayesian classifier decisions , first by comparing the probability of the size and weight to height to determine a person represented by two-dimensional vector is male or female , and then one by one with known gender data comparison, the statistical error rate can be . Then change the prior probability , repeat the above process , the results of the changes observed data . Bayesian classifier with the minimum risk decision-making , first find the minimum error rate using Bayesian classifier to get the conditional probability then artificially given decision table , according to the formula to calculate conditional risk and then one by one more conditional risk , to find ambassador to the conditions of minimum risk decision making (ie classification) . Finally, the results obtained with the classification by-side comparison of the raw data have been aware of SD error rate . )

基于MATLAB的2PSK调制,模擬錯誤率(MATLAB-based 2PSK modulation, analog error rate)

LPC program example