Abstract
In this paper, the concept of scalable non-uniform cellular automata (CAs) is discussed. The scalability of CA refers to its ability to accommodate more number of cells keeping the CA’s dynamic behaviour unchanged. That is, a CA with n cell, converges to point state attractor from any seed also converges to point state attractor when another few cells are added. Using scalability of CA, a CA based scalable pattern classifier is introduced.
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Notes
- 1.
A rule \(\mathcal {R}\) is said to be right independent rule, if each sibling pairs of RMTs r, s have same next state value either 0 or 1 that is \(\mathcal {R}[r]\) = \(\mathcal {R}[s]\).
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Naskar, N., Das, S. (2016). Scalability of Non-uniform Cellular Automata Having only Point State Attractors. In: El Yacoubi, S., Wąs, J., Bandini, S. (eds) Cellular Automata. ACRI 2016. Lecture Notes in Computer Science(), vol 9863. Springer, Cham. https://doi.org/10.1007/978-3-319-44365-2_6
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DOI: https://doi.org/10.1007/978-3-319-44365-2_6
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