DocumentCode
1907829
Title
Self-generating vs. self-organizing, what´s different?
Author
Wen, W.X. ; Pang, V. ; Jennings, A.
Author_Institution
Telecom Res. Lab., Clayton, Vic., Australia
fYear
1993
fDate
1993
Firstpage
1469
Abstract
Comparisons between the self-generating neural network (SGNN) and the self-organizing neural network (SONN) are performed. Although the SGNN concept is developed from SONN, the results obtained show that it has significant advantages when compared with SONN. These include simplicity of design methodology, greater speed for both training and testing, higher accuracy of clustering/classification, and better generalization capability. An analysis is conducted to investigate why SGNN is superior to SONN
Keywords
generalisation (artificial intelligence); learning (artificial intelligence); neural nets; self-adjusting systems; classification; clustering; generalization; learning; self-generating neural network; self-organizing neural network; Algorithm design and analysis; Australia; Clustering algorithms; Design methodology; Humans; Neural networks; Neurons; Organizing; Telecommunications; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298773
Filename
298773
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