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A way of combining SVM(Support Vector Machine) with Supervised Subset Density Clustering is proposed in this paper. How to minimize the training set of SVM by means of clustering is researched. Original center positions are of great importance to clustering accuracy. However the traditional clustering center choosing algorithm doesn't work properly when the same kind of samples aren't closely-spaced...
In this paper, we present a new available bandwidth measurement method with the characters of fast-convergence and high-accuracy, which is the improvement of Pathload. Pathload sends probe stream at specific rate and estimates the available bandwidth from the inference of self-induced congestion. Contrary to traditional Pathload method, the new method infers the congestion from two parameters, which...
For the purpose of improving the localization accuracy of bistatic sonar in some districts such as baseline district, side districts of transmitting and receiving stations, the most effective method is to increase the amount of the transmitting and receiving stations so that the multistatic sonar system is formed. Multistatic TOL algorithm and BOL algorithm, which are comparatively mature by far contains...
Using the characteristic of nonlinear function approach of CMAC neural network in cluster node, a novel model of comprehensive calibration, which aiming to improve the static state output characteristic of sensor nodes, was presented. Correction model of sensor nodes and comprehensive calibration model of cluster node were set up. The arithmetic is demonstrated, according to the simulation results,...
Network traffic analysis based on flows plays an important role in network monitoring and P2P identification. They are all grounded in flow counting and differ in how to count. Timeout detecting is a major strategy to identify termination of flows and can influence the validity of flow counting. The algorithms for counting flow based on Hash method can't deal with timeout problems perfectly. In this...
In this paper, Level Set Method is introduced including its advantages and disadvantages. Then the key process of Particle Level Set Method is particularly introduced including particle initialization, particle re-distribution in normal direction of the interface, reduction of error, and particle reseeding. At last some typical Level Set examples of different grid numbers and some typical Particle...
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