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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2015 Vol. 5(4): 339-343 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2015.V5.531

Effect of Patten Coding on Pattern Classification Neural Networks

Tomohiro Tanno, Kazumasa Horie, Takaaki Kobayashi, and Masahiko Morita
Abstract—A recent practical research reported that a layered neural network when applies pattern coding, which is a method to convert analogue input value into a multidimensional binary pattern, has a high capability of pattern classification. However, it does not conduct sufficient basic analysis; thus, the effect of pattern coding is unclear. The present study examines the effectiveness of pattern coding in pattern classification. Numerical experiments on two-dimensional two-class classification problems show that a multilayer perceptron can learn complex decision boundaries when pattern coding is applied. The results also indicate that pattern coding is also effective for a simple perceptron if selective desensitization is applied jointly.

Index Terms—Neural networks, pattern classification, pattern coding, selective desensitization.

T. Tanno, K. Horie, and T. Kobayashi are with the Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan (e-mail: tanno@bcl.esys.tsukuba.ac.jp, horie@bcl.esys.tsukuba.ac.jp, takaaki@bcl.esys.tsukuba.ac.jp).
M. Morita is with the Faculty of Engineering, Information and Systems, University of Tsukuba, Tsukuba, Ibaraki 305-8573, Japan (e-mail: mor@bcl.esys.tsukuba.ac.jp).

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Cite: Tomohiro Tanno, Kazumasa Horie, Takaaki Kobayashi, and Masahiko Morita, "Effect of Patten Coding on Pattern Classification Neural Networks," International Journal of Machine Learning and Computing vol. 5, no. 4, pp. 339-343, 2015.

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