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.