By Topic

A Speech Recognition Based on Quantum Neural Networks Trained by IPSO

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Lihui Fu ; Fac. of Electron. & Electr. Eng., Huaiyin Inst. of Technol., Huaian, China ; Junfeng Dai

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.

Published in:

Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on  (Volume:2 )

Date of Conference:

7-8 Nov. 2009