Abstract
This paper presents a pattern classifier to handle real valued patterns. A special class of Fuzzy Cellular Automata (FCA), referred to as Fuzzy Multiple Attractor Cellular Automata (FMACA), is employed to design the pattern classifier. The analysis reported in this paper has established the FMACA as an efficient pattern classifier for real valued patterns. Excellent classification accuracy and low memory overhead of FMACA based pattern classifier have been demonstrated through extensive experimental results.
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Maji, P., Chaudhuri, P.P. (2004). FMACA: A Fuzzy Cellular Automata Based Pattern Classifier. In: Lee, Y., Li, J., Whang, KY., Lee, D. (eds) Database Systems for Advanced Applications. DASFAA 2004. Lecture Notes in Computer Science, vol 2973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24571-1_46
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DOI: https://doi.org/10.1007/978-3-540-24571-1_46
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21047-4
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