Game-theory--Nash-equilibrium

刘宝碇《不确定规划及应用》第4章例4.4的matlab程序。内容简单，但可以有效的帮助初学者理解随机模拟的原理。(Liu anchor " uncertain Planning and Applications" in Chapter 4 Example 4.4 matlab program. Content is simple, but can effectively help beginners understand the principles of stochastic simulation.)

说明：  用sinc插值和最近领域插值完成距离弯曲校正的完整程序和几篇弯曲校正文章(Using sinc interpolation and nearest domain interpolation to complete the complete program and several bending correction articles)

一个可图片中文字进行识别的matlab实例程序，具有很不错的识别率(A picture in the text to identify the matlab example programs, with very good recognition rate)

UKF code for Unscented Kalman Filter sigma calculation(UKF code)

FastICA算法的盲源分离程序，为函数，输入混合信号矩阵即可。(FastICA algorithm of blind source separation program for the function, the input signal matrix can be mixed.)

The firefly algorithm (FA) is a metaheuristic algorithm, inspired by the flashing behaviour of fireflies. The primary purpose for a firefly s flash is to act as a signal system to attract other fireflies. Xin-She Yang formulated this firefly algorithm by assuming:[1] All fireflies are unisexual, so that one firefly will be attracted to all other fireflies Attractiveness is proportional to their brightness, and for any two fireflies, the less bright one will be attracted by (and thus move to) the brighter one however, the brightness can decrease as their distance increases If there are no fireflies brighter than a given firefly, it will move randomly. The brightness should be associated with the objective function. Firefly algorithm is a nature-inspired metaheuristic optimization algorithm.

这是模式识别中最小错误率Bayes分类器设计方案。 自行完善了在不同先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。 全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。 调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。 调用最小错误率贝叶斯分类器决策子函数时，根据先验概率数组，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。 主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小错误率贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到不同先验概率条件下错误率的统计。 (This is the minimum error rate pattern recognition Bayes classifier design. Self- improvement prior probability in different conditions , male , female and total error rate error rate statistics , into which each array . All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions . Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector third step is to application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function . Call the minimum error rate decision Functions Bayesian)

这是一个matlab人脸识别程序代码，有GUI界面(This is a face recognition matlab code, there is a GUI interface)

基于TDOA定位，用卡尔曼滤波器的算法减小误差更准确地的去追踪和定位目标。(use the EKF algorithm to track the localization)

本程序为将分水岭算法应用于图像分割中，实现了算法仿真(This program is the watershed algorithm is applied to image segmentation algorithm implemented simulation)