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. © Springer-Verlag 2004.
Cite
CITATION STYLE
Maji, P., & Pal Chaudhuri, P. (2004). FMACA: A Fuzzy Cellular Automata based pattern classifier. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2973, 494–505. https://doi.org/10.1007/978-3-540-24571-1_46
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