Optimization of MLP/BP for character recognition using a modified alopex algorithm

  • Authors:

  • Hirohito Shintani;Masatake Akutagawa;Hirofumi Nagashino;Abhijit S. Pandya;Yohsuke Kinouchi

  • Affiliations:

  • (Correspd. Tel./Fax: +81 88 656 7475/ E-mail: hsintani@ee.tokushima-u.ac.jp) Faculty of Engineering, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, 770-8506, Japan;Faculty of Engineering, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, 770-8506, Japan;School of health sciences, The University of Tokushima, 3-18-15, Kuramoto, Tokushima, 770-8509, Japan;Department of Computer Science and Engineering, Florida Atlantic University, Boca Raton, Florida 33431, USA;Faculty of Engineering, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, 770-8506, Japan

  • Venue:
  • International Journal of Knowledge-based and Intelligent Engineering Systems
  • Year:
  • 2007

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Abstract

It is difficult to determine the recognition mechanism in the neurons of a neural network trained for pattern recognition due to the non-linear nature of neural networks. This paper describes a recognition mechanism of a four-layer back propagation neural network using Alopex algorithm. We have developed a small-scale, four-layered neural network model for simple character recognition, which can recognize the patterns transformed by affined conversion. Alopex algorithm is an iterative and stochastic processing method, which was proposed for optimization of a given cost function. In this case the receptive fields of the neurons in the output layers are obtained using the Alopex algorithm.