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 