Title :
Neuro-symbolic Performance Comparison
Author :
Sathasivam, Saratha
Author_Institution :
Sch. of Math. Sci., Univ. Sains Malaysia, Minden, Malaysia
Abstract :
The convergence property for doing logic programming in Hopfield network can be accelerated by using sign constrained method and new modified learning rule. In this paper we compare the performance of doing logic programming task using the both methods. The capacity and attractor performance of these networks is tested by using computer simulations. In this paper, it has been proven by computer simulations that the sign constrained method provides better solutions.
Keywords :
Hopfield neural nets; logic programming; Hopfield network; computer simulations; logic programming; modified learning rule; neuro-symbolic performance comparison; sign constrained method; Application software; Associative memory; Computer applications; Computer networks; Computer simulation; Convergence; Electronic mail; Logic programming; Neural networks; Neurons; Hopfield; logic programming; new modified learning rule; sign constrained method;
Conference_Titel :
Computer Engineering and Applications (ICCEA), 2010 Second International Conference on
Conference_Location :
Bali Island
Print_ISBN :
978-1-4244-6079-3
Electronic_ISBN :
978-1-4244-6080-9
DOI :
10.1109/ICCEA.2010.8
