DocumentCode
2623334
Title
A learning algorithm for MLN with dynamic neurons
Author
Li, Haizhou ; Xu, Bingzheng
Author_Institution
Inst. of Radio Autom., South China Univ. of Technol., Guangzhou, China
fYear
1991
fDate
18-21 Nov 1991
Firstpage
523
Abstract
A multilayer network architecture with dynamic neurons which have multilocal feedbacks is built. The proposed network can be trained to memorize sequential patterns. A learning algorithm which is more effective and easier to implement is derived. Some experiments on speech recognition of Chinese digits designed to explore the capabilities of the proposed networks to learn dynamic properties of time-varying data are discussed. The performance of dynamic neurons with different time delay periods is also shown
Keywords
learning systems; neural nets; parallel architectures; speech recognition; Chinese digits; dynamic neurons; feedbacks; learning algorithm; multilayer network architecture; sequential pattern memorization; speech recognition; time-varying data dynamic properties learning; Added delay; Automation; Delay effects; Hysteresis; Neural networks; Neurofeedback; Neurons; Nonhomogeneous media; Speech recognition; State feedback;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991. 1991 IEEE International Joint Conference on
Print_ISBN
0-7803-0227-3
Type
conf
DOI
10.1109/IJCNN.1991.170453
Filename
170453
Link To Document