Input: Initial random weights; and input bias b
(1)Take th learning sample ( th and )
(3)Calculate the final output and error
(4)Update the weights by using excitatory rule
(5)Update the weights by using inhibitory rule
(6)If of training patterns then and proceed to the first
(7)Let epoch = epoch + 1 and
(8)If the stop criterion has not satisfied proceed to the first
Algorithm 1: Proposed SNP algorithm.