tx_modulate

本文中含有大量的matlab程序，包含小波变换的各种方法(This article contains a lot of matlab program, including the various methods of wavelet transform)

一个瑞利衰落信道容量的测试模型，包括两个m文件和一个说明文档。(A Rayleigh fading channel capacity of the test model, including a description of two m files and documents.)

一个讲述MATLAB基础的ppt格式的教程，内容比较详尽(About the basis of a MATLAB tutorial ppt format, content, more detailed)

用Matlab实现了常见的几种滤波算法：中位值滤波，递推平均滤波，一阶滞后滤波等算法。可以直接运行(Using Matlab to achieve several common filtering algorithms: median filtering, average filtering recursive, first-order lag filtering algorithm. Can run)

matlab中值滤波，数字图像处理源代码(median filter matlab, digital image processing source code)

精通Matlab教程，内容详细，每个命令有详细讲解和代码示例(Proficient in Matlab tutorials, detailed, each command has the detailed explanation and code examples)

这是一个贝叶斯分类器，用于人工智能的科研学习和工作，有例子可以参考(Bayesian classifier, artificial intelligence for research study and work, there are examples you can refer to)

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.

Eulers Method Ordinary Differential Equations

本程序用于对干涉条纹进行滤波，二值化，骨骼化，最后为求得条纹间距而得到一个像素宽度的图像(This procedure is used to filter the interference fringe, thresholding, skeletonization, and finally to obtain the fringe spacing and width of the image by one pixel)