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5 Conclusion
This paper reports the pattern recognizable capability of
Cellular Automata
Machine
(
CAM
). Extensive experimental results reported in this paper confirm
that the sparse network of
CAM
out-performs the conventional Hopfield Net.
References
1. J. J. Hopfield,
“Pattern Recognition computation using action potential timings
for stimulus representations”,
Nature, 376: 33-36; 1995.
2. M. Chady and R. Poli,
“Evolution of Cellular-automaton-based Associative Mem-
ories”,
Technical Report no. CSRP-97-15, May 1997.
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).
4. R. Raghavan,
“Cellular Automata In Pattern Recognition”,
Information Science,
70: 145-177; 1993.
5. K. Morita, S. Ueno,
“Parallel generation and parsing of array languages using re-
versible cellular automata”,
Int. J. Pattern Recognition and Artificial Intelligence,
8: 543-561; 1994.
6. E. Jen,
“Invariant strings and Pattern Recognizing properties of 1D CA”,
Journal
of statistical physics, 43, 1986.
7. S. Wolfram,
“Theory and application of Cellular Automata”,
World Scientific,
1986.
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.
9. N. Ganguly, A. Das, P. Maji, B. K. Sikdar, and P. Pal Chaudhuri,
“Evolving Cellu-
lar Automata Based Associative Memory For Pattern Recognition”,
International
Conference on High Performance Computing, Hyderabad, India, 2001.
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.
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, Yoko-
hama National University, Japan, 2001.
12. J. Hertz, A. Krogh and R. G. Palmer,
“Introduction to the theory of Neural com-
putation”,
Santa Fe institute studies in the sciences of complexity, Addison Wesley,
1991.
