The conjugate gradient optimization algorithm is combined with the modified back propagation algorithm to yield a computationally efficient algorithm for training multilayer perceptron (MLP) networks (CGFR/AG). The computational efficiency is enhanced by adaptively modifying initial search direction as described in the following steps: (1) Modification on standard back propagation algorithm by ...

In this paper, an efficient face recognition system based on sub-window extraction algorithm and recognition based on principal component analysis (PCA) and Back propagation algorithm is proposed. Our proposed method works on two phases: Extraction phase and Recognition phase. In extraction phase, face images are captured from different sources and then enhanced using filtering, clipping and hi...

This paper addresses a classification task of pattern recognition by combining effectiveness of evolutionary and gradient descent techniques. We are proposing a hybrid supervised learning approach using real-coded GA and back-propagation to optimize the connection weights of multilayer perceptron. The following learning algorithm overcomes the problems and drawbacks of individual technique by i...