binary-lms

Bayesian Alpha Matting

说明：  cnp网络算法 运用matalb仿真程序 紧供参考(cnp network algorithm to use tight matalb simulation program for reference)

说明：  文件中代码实现小波图像融合，对低频和高频系数采用不同准则，有详细说明(File code implementation of wavelet image fusion, of the low and high frequency coefficients using different criteria, are detailed)

在此建立了车辆悬架的模拟模型，并对其进行了仿真研究(In this paper, the simulation model of vehicle suspension is established and simulated.)

LPC vocoder LPC vocoder with several option Graphical user interface Also included several .wav file as example

可自行设置参数产生SCM信道，支持MIMO等功能(can set your own parameter to create SCM channel,support MIMO an other function.)

This program counts the occurrence of specified patterns in the input strands and produces a report for each pattern. The first input to this program will be an integer indicating how many patterns will be provided (call this N). The next N words to this program will be patterns of nucleobases to search for. Following the patterns will be a sequence of strands terminated by the word "end" as before.

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.

kalman滤波器实现目标跟踪，对研究数据融合，目标跟踪有一定的参考价值(target tracking using kalman filter)

kmeans聚类，用于时间序列无监督聚类(kmeans clustering for unsupervised clustering time series)