Hybrid of the approximate neural network with sparse RAM and Fisher´s linear discriminant for face recognition

In this paper, a face recognition approach based on the hybrid of the approximate neural network with sparse RAM (SN-tuple) and Fisher´s linear discriminant (FLD) is presented. Firstly, the data of original face images are imported into the SN-tuple to classify these faces roughly. Then FLD, a classical statistical pattern recognition method, are used to classify these faces precisely. Experimental results demonstrate that this proposed approach achieves better performance than the SN-tuple and FLD for face recognition respectively.