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Online hot topic detection is a significant research field in web data mining, which can help people make policy decision or benefit to people's daily life. Actually, in recent years more and more hot topics are arising from BBS, often referred as online forum. BBS provide a communication platform for people to discuss and express their views. It's obvious that forecasting the hotness topics on BBS...
A new multi-scale image segmentation algorithm based on nonsubsampled contourlet transform (NSCT) and simplified plus coupled neural network (SPCNN) has been discussed in this paper. Comparing with plus coupled neural network (PCNN), the SPCNN algorithm can decrease the complexity of adjusting parameters significantly. First we combine susan edge detector with SPCNN, more accurate result can be obtained...
In this paper, a new automatic method for constructing and evolving complex network is proposed. This method uses the concept of complex networks (mainly scale-free networks) and combines the essence of immune programming with particle swarm optimization algorithm. The structure of a complex network genotype is evolved using immune programming algorithm with specific parameters, and the fine tuning...
3D data registration and classifier are two important components in face recognition system. Aiming at the current methods' handicaps such as slow convergence and easiness of getting into local optimization, this paper presents a novel face recognition method using filled function, one of the effective deterministic methods. It gives a modified concept of filled function based on Ge, and proposes...
3D data registration and classifier are two important components in face recognition system. Aiming at the handicaps in current methods such as slow convergence or easiness of getting into local optimization, this paper works out a novel face recognition method combining filled function method, which can find a lower local minimizer by leaving the local minimizer previously found. By repeating these...
This paper introduces a novel adaptive PN-code acquisition for GPS DSSS receivers, which is compared with traditional classical PN-code acquisition and proven better in general sense. It adopts a two-dimensional characteristic method, in which the parallel-processing is used in frequency-domain as the code correlator and in time-domain the steps of DCO are adaptively controlled to track the offset...
To meet the robustness of the fault diagnosis algorithm for identifying the novel fault pattern, the method, which combines the supervised classification and unsupervised classification, is proposed in this paper. As the supervised classification, Learning vector quantity neural network is employed to classify sensor mode. As the unsupervised classification, subtractive clustering is applied to identify...
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