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Aimed at PSO's defect of prematurity, an improved particle swarm optimization(IPSO) is presented. The new arithmetic has better optimization performance by adding random data to premature particles' speed and position. It was applied to the parameter learning and training of Quantum Neural Network(QNN), and a higher efficiency speech recognition system which based on IPSO-QNN was established. The experimental results of MATLAB simulation showed that the new arithmetic did a better job in speech recognition rate and speed which make the best of faster quantum neural computation and PSO's global optimization ability.
Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on (Volume:2 )
Date of Conference: 7-8 Nov. 2009