SVM

小波阈值去噪，比较了软阈值，硬阈值及当今各种阈值计算方法和阈值函数处理方法的性能，通过信噪比及均方差的比较，得出各种的算法的优劣。(Wavelet threshold denoising compared soft threshold and hard threshold and the current method of calculating the various thresholds and thresholds approach the performance of function, through the signal to noise ratio and mean square deviation of the comparison, the various algorithms advantages and disadvantages.)

说明：  主要包括两个源代码。其中一个源代码是识别程序的，另一个是一个矩阵类库的。(Consists of two source code. One is to identify the program source code, and the other is a matrix class library.)

这是偶最近研究的成果，正准备写论文的，关于一类单关节机器人的基于滤波器的滑模变机构控制策略，有完整的控制器和对象S函数，以及整个系统的模块文件，好处不用我说拉！(This is the duality results of recent studies, is preparing to write papers on a class of single-joint robot filter based sliding mode control strategy, the controller and have a complete object S function, as well as the entire system module file, benefits is not necessary for me la!)

Ant Colony Algorithm for Traveling Salesman Problem

Addition and subtraction of signals matlab code

Binary cat search optimization algorithm

采用非线性主分量方法对育信号进行分离的算法。运行环境MATLABR2008B。程序+报告都在里面(Nonlinear principal component method of fertility signal separation algorithms. Operating environment MATLABR2008B. Procedure+ reports inside)

一个FastICA的实例程序，希望对学习ICA的同志有所帮助(FastICA instance a program, I hope to learn ICA comrades help)

chirp signal generator

In this paper, we introduce a new machine-learning-based data classification algorithm that is applied to network intrusion detection. The basic task is to classify network activities (in the network log as connection records) as normal or abnormal while minimizing misclassification. Although different classification models have been developed for network intrusion detection, each of them has its strengths and weaknesses, including the most commonly applied Support Vector Machine (SVM) method and the Clustering based on Self-Organized Ant Colony Network (CSOACN). Our new approach combines the SVM method with CSOACNs to take the advantages of both while avoiding their weaknesses. Our algorithm is implemented and evaluated using a standard benchmark KDD99 data set. Experiments show that CSVAC (Combining Support Vectors with Ant Colony) outperforms SVM alone or CSOACN alone in terms of both classification rate and run-time efficiency.