Title :
Fault-tolerant design of neural networks for solving optimization problems
Author :
Tohma, Yoshihiro ; Koyanagi, Yoichi
Author_Institution :
Dept. of Inf. & Commun. Eng., Tokyo Denki Univ., Japan
fDate :
12/1/1996 12:00:00 AM
Abstract :
First, the incorporation of the alternative ways of representing the solution to the traveling salesman problem by neural network is proposed to deal with the asymmetric tolerance of neural networks to unidirectional faults. Next, in order to cope with the simultaneous occurrence of a s-a-0 and s-a-1 faults, the triplication scheme with a proper merging function is considered. Finally, the combination of the alternative representations and the triplication scheme is used
Keywords :
fault tolerant computing; logic testing; neural nets; optimisation; travelling salesman problems; asymmetric tolerance; fault-tolerant design; merging function; neural networks; optimization problems; s-a-0 faults; s-a-1 faults; traveling salesman problem; triplication scheme; unidirectional faults; Associative memory; Cities and towns; Design optimization; Fault tolerance; Feedforward neural networks; Feedforward systems; Merging; Neural network hardware; Neural networks; Traveling salesman problems;
Journal_Title :
Computers, IEEE Transactions on