数字技术与应用Issue(4)：109-110,2.
粒子群优化 RBF 神经网络的语音识别研究
Optimization of RBF Neural Network based on PSO in speech recognition
王凯1
作者信息
- 1. 四川大学电气信息学院 四川成都 610065
- 折叠
摘要
Abstract
An improved Radial Basis Function (RBF) neural network has been proposed to obtain the center and width of hidden layer basis function by using supervised particle swarm optimization (PSO) the clustering learning methods. This improved RBF neural network has been used for speech recognition and corresponding speech recognition simulation system has been built. Experimental results demonstrate that the PSO-RBF neural network has a higher recognition rate and has a shorter training time compared with standard RBF neural network.关键词
粒子群/径向基/神经网络/语音识别Key words
Particle swarm optimization/Radial basis function Neural network/Speech recognition分类
信息技术与安全科学引用本文复制引用
王凯..粒子群优化 RBF 神经网络的语音识别研究[J].数字技术与应用,2013,(4):109-110,2.
