BImplementation of high speed face recognition based on karhunen loeve transform and fisher's discriminant, radial basis function of echo state neural network

Recently proposed approach to recognitize facial expressions have been proposed Jager with the so called Echo State Neural Network (ESNN). The ESSN approach assumes a sort of "block box" operability of the network and clients a broad applicability to several different problems using same principle, here we proposes a simplified version of ESNN which we call a simple echo state network which exhibits good results in memory capacity and facial matching and recognition which allows a better understating of the capability and restriction of ESNN. ESSN gives promising result when the input are distorted. Simulation results show that a proposed system (ESNN) achieves a excellent performance with high training and recognition speed.