NBLR

利用Newton迭代法求解f(x)=(x-1)(x-2)(x-3)=x3-6x2+11x-6的根(solve the root of function: f(x)=(x-1)(x-2)(x-3)=x3-6x2+11x-6 by using Newton method)

这是一个非常全面的关于FFT的程序，适用于matlab分析。(This is a very comprehensive program on the FFT for matlab analysis.)

高斯核函数的源程序代码，列出5种情况，程序包涵仿真图等。值得拥有。(Gaussian kernel function of the source code, listing 5 kinds of circumstances, program includes the simulation diagram, etc. Worth having. )

说明：  matlab 的 ofdm 系统程序 仿真(matlab simulation of ofdm system program)

短时能量估计以及过零率估计，对声音信号的处理很有帮助，希望对大家有所帮助。(Short-term energy estimates and zero crossing rate is estimated that the processing of sound signals is helpful, we hope to help.)

用SMo求解svm的算法，有最大间隔还有高斯核，多项式核，得到SMO还是比较简单的算法(using SMO to solve SVM)

计算信号检测时的ROC曲线,计算结果比较准确，完全符合要求。(Computed the ROC curves.)

matlab中值滤波，滤去高斯噪声白噪声等相关噪声信号(matlab median filtering, filtered Gaussian noise, white noise and noise signal)

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.

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