DocumentCode :
3250642
Title :
Self-generating neural networks
Author :
Wen, Wilson X. ; Liu, Huan ; Jennings, Andrew
Author_Institution :
Telecom Res. Lab., Clayton, Vic., Australia
Volume :
4
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
779
Abstract :
A method for generating neural networks automatically is proposed. Not only the weights of the connections but also the structure of the network, including the number of neurons, the number of layers, and the interconnections among the neurons, is learned from the training examples. Issues of optimization and pruning of the generated networks are investigated. An experimental system has been implemented based on the proposed method and some experimental results and comparisons between this method and other methods are also given
Keywords :
learning by example; optimisation; self-organising feature maps; generated networks; interconnections; layers; learning from examples; neurons; optimization; pruning; self-generating neural nets; weights; Artificial intelligence; Feedforward neural networks; Humans; Neural networks; Neurons; Resonance; Self-organizing networks; Telecommunications; Tree data structures; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.227223
Filename :
227223
Link To Document :
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