American Journal of Applied Sciences

Winner-Take-All Neural Network with Massively Optoelectronic Interconnections

Wissam H. Ali, Ahmed N. Abdalla and Wa'l H. Ali

DOI : 10.3844/ajassp.2009.268.272

American Journal of Applied Sciences

Volume 6, Issue 2

Pages 268-272

Abstract

The increased interconnection density, bandwidth, nonlocality and fan-out-fan-in offered by optics over conventional electronic technologies make it a very attractive medium for a variety of application particularity in the field of communication system implementation for all types of computing engines is achieved. This is especially true for neural networks in which the demand for communication resources is extremely high. In this study, the implementation of a neural network that exploits an optical interconnect to perform a real task is described. A pnpn semiconductor device has been connected in parallel with a common load resistance for optical switching. When illuminated, only this device with maximum input will turn on. The voltages across the other devices drop and inhibit their switching ability. With suitable biasing, the winning device can be recall at any time. The result shows, a much faster response (<10ns) can be obtained from thyristors made of III-V compound semiconductors, because their carrier lifetime is considerably shorter than in silicon. With III-V photothyristor, it is possible to combine light emission (even lasing) and photothyristor action in the same unit.

Copyright

© 2009 Wissam H. Ali, Ahmed N. Abdalla and Wa'l H. Ali. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.