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The solution of multi-output LS-SVR machines follows from solving a set of linear equations. Compared with ε-intensive SVR, it loses the advantage of a sparse decomposition. In order to limit the number of support vectors and reduce the computation cost, this paper presents a decremental recursive algorithm for multi-output LS-SVR machines. This algorithm removes one sample one time and large-scale...
Mass of the training samples and setting parameters of SVM artificially will affect badly the efficiency to find an optimal decision hyper plane for SVM. In this paper, FCM clustering algorithm and heuristic PSO algorithm are applied to Intrusion Detection. FCM clustering algorithm is designed to help SVM to find the optimal training samples from vast amounts of data; heuristic PSO algorithm is designed...
Vector Quantization (VQ) is a useful tool for data compression and can be applied to compress the data vectors in the database. The quality of the recovered data vector depends on a good codebook. Mean/residual vector quantization (M/RVQ) has been shown to be efficient in the encoding time and it only needs a little storage. In this paper, Clonal Selection Algorithm for Image Compression (CSAIC) is...
This paper introduces the use of combined neural network model to guide model selection for detection of weak signal. It has been found that digital filters are not suitable for processing weak signals in noise, while wavelet neural network (WNN) is used to analyze weak digital signal and extract small-features. WNN is a time-frequency analysis adaptive system, which detects the subtle small changes...
In order to experiment the performance of some popular ANN algorithms to OMIS (Operational Modular Imaging Spectrometer) hyperspectral image, three widely used ANNs, including Back Propagation Neural Network (BPNN), Radial Basis Function Neural Network (RBFNN), Fuzzy ARTMAP network and their improvements, are employed and compared. It is concluded that ANN classifiers perform much better than traditional...
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