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Parameters selection of support vector machine is a very important problem, which has great influence on the performance of support vector machine. Particle swarm optimization is an efficient algorithm and it is broadly used in many research areas like pattern recognition and so on. In order to improve the learning and generalization ability of support vector machine, a method for searching the optimal...
A structure equivalent fuzzy radial basis function (FRBF) neural network with five layers is proposed in this paper. A two stage algorithm for the parameters learning of the network is presented, which first determine the center value and width of the membership function according to the classification information of training samples, and then adjusts the weights between the fourth layer and the fifth...
There are two problems when conditional T-S fuzzy neural network is used directly in speech recognition system. One is the rule disaster problem, that is, the rule number will increase exponentially with the increase of input dimensions. Another problem is the network reasoning failure resulted from input dimensions too large. The paper presented an improved algorithm of T-S fuzzy neural network....
The measurement of Mel spectrum distortion is a kind of warped frequency spectrum distortion measure. Using Mel frequency scale can reflect sufficiently the nonlinear perceptive characteristic of human hearings to frequency and amplitude. It can also reflect the frequency analysis and spectrum synthesis characteristics when human hear complex sounds. Aiming at speech recognition of isolated words,...
Speech endpoint detection is an important step in the field of speech analysis, speech synthesis and speech recognition. This paper proposed an endpoint detection algorithm, which used amplitude entropy, spectral entropy and frame energy as feature parameters and utilized RBF neural network as a feature classification system. 170 sentences are used as testing data to detect speech endpoint, which...
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