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Kernel parameters selection of support vector machine is a very important problem, which has great influence on the performance of support vector machine. In order to improve the learning and generalization ability of support vector machine and enhance speech recognition system accuracy, a method of searching for the Gaussian kernel support vector machine optimal parameters(C, ?? ) based on particle...
Aim to the problems of fuzzy neural network depending on the initial conditions, the training time long, and being easy to fall into local minimum, this paper studied the combination of particle swarm optimization and fuzzy neural network, presented a fuzzy neural network model based on particle swarm optimization, and applied it in speech recognition system. This model improved the convergence speed...
For the blind source separation algorithm, choices of nonlinear function and step-size are very important. In this paper, we propose a novel natural gradient speech blind separation algorithm. The main ingredients are the use of a variable step-size technology and a nonlinear function based on Laplacian normal mixture distribution. Simulation results indicate the proposed method ensures steady state...
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