roidpoly

说明：  详细介绍如何使用matlab的一本书。非常的不错哦(Details of how to use matlab in a book. Oh, very good)

这是一道很基本的程序，一方面希望它对初学遗传算法的兄弟们有用（包含了遗传算法实现的大部分步骤，而且有详细的注释），另一方面旨在抛砖引玉， 在下浅见： 1、遗传算法在进行大规模计算时，数据交换量大，速度确实是一个瓶颈，就如这道程序，在种群规模50，进化代数1000时运行需要40秒左右(cpu:duron 1G),当然，小弟编程能力弱，望各位大侠指教啊，或帮我修改一下这道程序 (This is a very basic procedure, While they want it beginner GA brothers useful (including the genetic algorithm to achieve the most steps and a detailed note), on the other hand aims to attract the next suggestions : 1. GA conducting large-scale calculations, the data exchange capacity, speed is a bottleneck, as this practice. 50 in population size, the evolution of algebra required for the operation of 1000 when about 40 seconds (cpu : duron 1G), Of course, the younger programming weak, and hopes to enlighten ah Shanhaiguan, or help me rephrase this practice)

这是TD算法的逆过程，首先将时间序列，划分为相邻点的短序列，当然此时的拟合误差为0，因为第一点和第二点的连线，原始点都落在线段上。将相邻两个线段连接起来，此时每条线段包含三个原始点，计算中间那个点的拟合误差。这样，所有这些三个点的线段中的中间点的拟合误差计算出来后，找出误差最小且误差小于阀值R的分段，作为第一条包含三个点的线段。 在上面的基础上，第一条分段同样的和相邻线段连接，然后计算每一条分段的拟合误差，再找出误差最小且小于阀值R的分段，作为第二个分段。依次方式循环，直到所有分段的拟合误差都小于阀值R，分段结束。 (This is the reverse process of TD algorithm, the first time series is divided into short sequences adjacent dots, of course fitting error is zero at this time, because the first and second points of connection, the original point fall line on. The two adjacent segments are connected, then each segment contains three original point, the intermediate fitting error calculated that point. Thus, after all these segments fitting error of three points in the intermediate point calculated to find the minimum error and the error is less than the threshold R segment, as the first line contains three points. Based on the above, the first segment and the adjacent line segment connecting the same, and then calculate a fitting error for each segment, and then find the smallest error and less than the threshold R segment, as the second segment . Followed by a cyclic manner until all segments fitting error is less than the threshold R, segment ends.)

一种改进型的PSO的机器学习算法实现，应用欧氏距离作为分类便准，KNN分类法实现分类(An improved PSO algorithm)

利用自然梯度算法，分数阶傅里叶变换计算方面,可以实现模式识别领域的数据的分类及回归。( Use of natural gradient algorithm, Fractional Fourier transform computing, You can achieve data classification and regression pattern recognition.)

自己根据网上已有程序改写的(127,115)RS编码，有详细的注释及对FPGA实现算法的改写(参考try123.m)，希望可以让大家少走弯路~~~((127,115) rs encoder/decorder with detailed annotations.)

Trade FX with SVM and Matlab

Normalized Cuts and Image Segmentation xp下的32位的绝对可以运行(Normalized Cuts and Image Segmentation xp under can run 32-bit absolute)

数字通信原理教程，里面有配套的matlab仿真程序，值得学习。(Principles of Digital Communication Guide, which has a matching matlab simulation program, worth learning.)

黄友瑞的智能优化算法书中的免疫算法源代码！！！！(Intelligent Optimization Algorithm Huang Yourui immune algorithm source code book! ! ! !)