sum_jl

说明：  基本的直方图绘制方法： （1）直方图的绘制； （2）直方图均衡化(The basic method of drawing histogram: (1) Draw the histogram (2) Histogram equalization)

error diffusion2 in matlab

Arquivo do Fastreport para implementaç ã o

数字滤波器的实现，矩形窗、汉宁窗、海明窗、布莱克曼窗等窗函数 (The realization of digital filters, rectangular window, Hanning window, Hamming window, Blackman window functions such as window)

toeplitz方程的求解算法，反卷积中所使用。x*h=y, 已经h,y,求x。(Equation toeplitz algorithm used in the deconvolution. x* h = y, has h, y, need to solve x)

经济类的实用的时间序列分析软件包，已经是目前最好的版本了。USCD_GARCH，可以研究非平稳时间序列数据。(kind of practical time series analysis software package, is the best current version. USCD_GARCH can study non-stationary time series data.)

Practical Genetic algorithms-Haupt-2004-261s

ensemble卡尔曼滤波模型，能很好的在matlab上运行，并有好的结果(ensemble Kalman filter model, can be a good run in matlab and have good results)

训练错误率和交叉验证错误率相等，在样本比较大时，这个结果是可以预期的；训练错误率一般低于测试错误率，但是当样本数据比较少时，实验也出现了意外，样本多的那组测试错误率比样本少的训练错误率还要小；在本实验中，同组数据的交叉验证错误率比独立测试错误率高，这个反常现象是因为样本的原因所致，交叉验证的样本小，而独立测试时所用训练样本数目大，因而出现这种情况。分类线上，fisher准则是一条直线，而贝叶斯分类器实际上是一个类似椭圆的封闭曲线；很明显，贝叶斯分类器比fisher分类器要好。(Training error rate and cross- validation error rates are equal, the larger the sample , this result is to be expected training error rate is generally lower than the test error rate , but when comparing the sample data came from the experiment there was an accident, that more samples group test error rate less than the training sample error rate is smaller In this experiment, the same set of data cross-validation error rate than independent test error rate, this anomaly is because the sample of reasons , cross-validation sample is small,And independent testing large number of training samples used , resulting in this situation.Classification online , fisher criterion is a straight line , while the Bayesian classifier is actually a closed curve similar to elliptical It is clear that the Bayesian classifier is better than the fisher classifier .)

基于遗传算法的多目标优化，matlab开发(Based on genetic algorithm for multi-objective optimization, matlab development)