Abstract:
:This paper studies the performance of single-layered neural networks. This study begins with the performance of single-layered neural networks trained using the outer-product rule. The outer-product rule is a suboptimal learning scheme, resulting under certain assumptions from optimal least-squares training of single-layered neural networks with respect to their analog output. Extensive analysis reveals the improvement on the network performance caused by its optimal least-squares training. The effect of the training scheme on the performance of single-layered neural networks with binary output is exhibited by experimentally comparing the performance of single-layered neural networks trained with respect to their analog and binary output.
journal_name
Biol Cybernjournal_title
Biological cyberneticsauthors
Karayiannis NB,Venetsanopoulos ANdoi
10.1007/BF00203135keywords:
subject
Has Abstractpub_date
1992-01-01 00:00:00pages
31-41issue
1eissn
0340-1200issn
1432-0770journal_volume
68pub_type
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