Simplified Intelligence Single Particle Optimization Based Neural Network for Digit Recognition

Abstract

To overcome the drawback of overly dependence on the input parameters in intelligence single particle optimization (ISPO), an improved algorithm, called simplified intelligence single particle optimization (SISPO), is proposed in this paper. While maintaining similar performance as ISPO, no special parameter settings are required by SISPO. The proposed SISPO was successfully applied to train neural network classifier for digit recognition. Experimental results demonstrated that, the proposed neural network training algorithm, simplified intelligence single particle optimization neural network (SISPONN), achieved less training error and test error than traditional BP algorithms like gradient methods.