Optical matrix-vector implementation of the content-addressable network.
The content-addressable network (CAN) is an efficient, intrinsically discrete training algorithm for binary-valued classification networks. The binary nature of the CAN network permits accelerated learning and significantly reduced hardware-implementation requirements. A multilayer optoelectronic CAN network employing matrix-vector multiplication was constructed. The network learned and correctly classified trained patterns, gaining a measure of fault tolerance by learning associative solutions to optical hardware imperfections. Operation of this system is possible owing to the reduced hardware accuracy requirements of the CAN learning algorithm.
Brodsky
S A
SA
Marsden
G C
GC
Guest
C C
CC