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In order to overcome inherent bugs of basic hidden markov model (HMM), a method of speech recognition based on fuzzy clustering neural network is presented. Based on the fuzzy system model, every state (HMM) is regarded as a fuzzy system in this method. With continuous frames character vector of speech signal as the system's input, the model can forecast the probability density function of the system's...
The training procedures of RBF neural network are faster than BP neural network and it has the global optimal ability. However, a key problem by using the RBF neural network approach is about how to choose the optimal the parameters of RBF neural network. Particle swarm optimization is introduced to select the parameters of RBF neural network. In the paper, particle swarm optimization and RBF neural...
Radial basis function (RBF) neural network is used to predict the blast furnace hot metal based on its characteristics such as fast convergence and global optimization. As hot metal silicon content had close relationship with furnace temperature, the change of temperature in furnace was reflected indirectly by hot metal silicon content. Newrbe function in Matlab was applied for function approximation...
The paper studies optimal boiler control based on artificial neural networks. The method below is a combinative arithmetic including RBF (radial basis function), BP (back propagation) and PID (proportional integral differential) control algorithm, which is efficient to adapt the nonlinear boiler burning system. Simulation result shows that this method has got the adaptive characters, and it can satisfy...
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