Abstract
Assuming a fast learning condition for an adaptive resonance theory (ART) type neural network, we have explored the effect of the vigilance parameter and the order function on the performance of the neural network for binary pattern recognition. A modified search order was developed for classification of binary alphabet characters and airplane classes and compared with the performance of the original ART-1 network for binary pattern recognition with and without the presence of noise. Our results suggest that the effect of noise on binary pattern recognition is solely dependent on the induced changes in the critical feature patterns when other control parameters remained the same.
Original language | English |
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Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
Editors | Simon Haykin |
Publisher | Publ by Int Soc for Optical Engineering |
Pages | 323-330 |
Number of pages | 8 |
ISBN (Print) | 0819406937 |
State | Published - 1991 |
Event | Adaptive Signal Processing - San Diego, CA, USA Duration: Jul 22 1991 → Jul 24 1991 |
Publication series
Name | Proceedings of SPIE - The International Society for Optical Engineering |
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Volume | 1565 |
ISSN (Print) | 0277-786X |
Conference
Conference | Adaptive Signal Processing |
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City | San Diego, CA, USA |
Period | 07/22/91 → 07/24/91 |