tspof_ga

it is a implementation of a chaotic map.the chaotic map nam is logistic map

MATLAB产生BPSK信号和FM信号。包括信号的成形滤波，频谱分析和功率谱分析(MATLAB generated BPSK signal and FM signals. Signal shaping filtering, spectrum analysis, power spectrum analysis)

garch工具箱 估计garch模型和garch参数。(garch toolbox very powerful useful toolbox recommended! ! !)

说明：  Edge detection result should be enhanced using linear method like Median filter to remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the centre of the pupil by counting the number of black pixels (zero value) of each column and row. Then get each row and column that has the maximum number of these black pixels. Then determine the center by simple calculation according to the image coordinate to set it correct on the image, consequently we can determine the radius of the pupil. Thus we can find the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms of circle and ellipse.

小波阈值降噪的matlab代码 里面有两个程序 一个比较了软硬阈值去噪 另外一个对多层小波分解的阈值去噪做了对比(Wavelet threshold denoising matlab code there are two programs a relatively soft and hard thresholding is another multi-layer wavelet threshold denoising to do a comparison)

restore search blotch

该程序通过模仿生物的遗传特点，解决全局最优解的问题(The program solves the problem of global optimal solution by imitating the genetic characteristics of organisms)

说明：  MATLAB仿真的分布式电源接入对于配电网的影响，潮流计算加了固定的pq(The Influence of MATLAB-based Distributed Power Connection on Distribution Network)

自适应滤波器的设计，包括LMS和RLS，两种方法，程序简单实用(Adaptive filter design, including LMS and RLS, two types of methods, procedures simple and practical)

说明：  假如数据中有N 个变量，而我们想抽取的样本的数量是M,那么在对数据进行抽样的时候，这种方法首先会把N个变量的设计空间均匀的划分开为M份，然后在每个划分好的区域中随机的抽取一点，最后，从这M个变量里，随机挑选之前选好的点，构成我们的样本(If there are n variables in the data, and the number of samples we want to extract is m, then when sampling the data, this method will first divide the design space of n variables into M parts evenly, and then randomly extract a point in each divided area. Finally, from the m variables, randomly select the previously selected points to form our sample)