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Cellular Automata Machine for Pattern Recognition

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Cellular Automata (ACRI 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2493))

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Abstract

This paper reports a Cellular Automata Machine (CAM) as a general purpose pattern recognizer. The CAM is designed around a general class of CA known as Generalized Multiple Attractor Cellular Automata (GMACA). Experimental results confirm that the sparse network of CAM is more powerful than conventional dense network of Hopfield Net for memorizing unbiased patterns.

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References

  1. J. J. Hopfield, “Pattern Recognition computation using action potential timings for stimulus representations”, Nature, 376: 33–36; 1995.

    Article  Google Scholar 

  2. M. Chady and R. Poli, “Evolution of Cellular-automaton-based Associative Memories”, Technical Report no. CSRP-97-15, May 1997.

    Google Scholar 

  3. J. H. Moore, L. W. Hahn, “Multilocus pattern recognition using one-dimensional cellular automata and parallel genetic algorithms”, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001).

    Google Scholar 

  4. R. Raghavan, “Cellular Automata In Pattern Recognition”, Information Science, 70: 145–177; 1993.

    Article  Google Scholar 

  5. K. Morita, S. Ueno, “Parallel generation and parsing of array languages using reversible cellular automata”, Int. J. Pattern Recognition and Artificial Intelligence, 8: 543–561; 1994.

    Article  Google Scholar 

  6. E. Jen, “Invariant strings and Pattern Recognizing properties of 1D C A”, Journal of statistical physics, 43, 1986.

    Google Scholar 

  7. S. Wolfram, “Theory and application of Cellular Automata”, World Scientific, 1986.

    Google Scholar 

  8. P. Pal Chaudhuri, D Roy Chowdhury, S. Nandi and S. Chatterjee, “Additive Cellular Automata, Theory and Applications, VOL. 1”, IEEE Computer Society Press, Los Alamitos, California.

    Google Scholar 

  9. N. Ganguly, A. Das, P. Maji, B.K. Sikdar, and P. Pal Chaudhuri, “Evolving Cellular Automata Based Associative Memory For Pattern Recognition”, International Conference on High Performance Computing, Hyderabad, India, 2001.

    Google Scholar 

  10. N Ganguly, P Maji, A Das, B K Sikdar, P Pal Chaudhuri, “Characterization of Non-Linear Cellular Automata Model for Pattern Recognition”, 2002 AFSS International Conference on Fuzzy Systems, Calcutta, India, 2002.

    Google Scholar 

  11. P Maji, N Ganguly, A Das, B K Sikdar, P Pal Chaudhuri, “Study of Non-Linear Cellular Automata for Pattern Recognition”, Cellular Automata Conference, Yokohama National University, Japan, 2001.

    Google Scholar 

  12. J. Hertz, A. Krogh and R. G. Palmer, “Introduction to the theory of Neural computation”, Santa Fe institute studies in the sciences of complexity, Addison Wesley, 1991.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science & Technology, Bengal Engineering College (D U), Howrah, India, 711103

    Pradipta Maji, Sourav Saha, Anup K. Roy & P. Pal Chaudhuri

  2. Computer centre, IISWBM, Calcutta, India, 700073

    Niloy Ganguly

Authors
  1. Pradipta Maji
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  2. Niloy Ganguly
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  3. Sourav Saha
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  4. Anup K. Roy
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  5. P. Pal Chaudhuri
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Systems and Communication, University of Milano-Bicocca, Via Bicocca degli Arcimboldi, 8, 20126, Milan, Italy

    Stefania Bandini

  2. Computer Science Department, University of Geneva, 24, Rue du General Dufour, 1211, Geneva 4, Switzerland

    Bastien Chopard

  3. Computer Science Institute Faculty of Sciences, University of Lausanne, 1015, Lausanne, Switzerland

    Marco Tomassini

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© 2002 Springer-Verlag Berlin Heidelberg

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Maji, P., Ganguly, N., Saha, S., Roy, A.K., Chaudhuri, P.P. (2002). Cellular Automata Machine for Pattern Recognition. In: Bandini, S., Chopard, B., Tomassini, M. (eds) Cellular Automata. ACRI 2002. Lecture Notes in Computer Science, vol 2493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45830-1_26

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  • DOI: https://doi.org/10.1007/3-540-45830-1_26

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44304-9

  • Online ISBN: 978-3-540-45830-2

  • eBook Packages: Springer Book Archive

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