An Adaptive Opto-electronic Neural Network for Associative Pattern Retrieval

✍ Scribed by F. Ahmed; A.A.S. Awwal

• Publisher: Elsevier Science
• Year: 1993
• Tongue: English
• Weight: 512 KB
• Volume: 17
• Category: Article
• ISSN: 0743-7315
• DOI: 10.1006/jpdc.1993.1023

✦ Synopsis

A novel adaptive trinary neural network model is proposed for associative pattern retrieval from incomplete data. Systematic analysis of the convergence mechanism for the character recognition problem is provided to illustrate the derivation of this novel adaptive thresholding scheme. The adaptive scheme with trinary input representation outperforms other associative retrieval schemes in terms of convergence and storage capacity. The inherent parallelism of this neural network architecture is exploited for a parallel optical implementation. The tremendous speed and free-space interconnection capability of optics results in a very efficient real-time character recognition system. The adaptive threshold scheme developed here may have far reaching implications for other neural networks in enhancing their learning and retrieval, speed, and accuracy. 1993 Academic Press, Inc.