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The Generative Capacity of Probabilistic Splicing Systems |
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PP: 1191-1198 |
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Author(s) |
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Mathuri Selvarajoo,
Sherzod Turaev,
Wan Heng Fong,
Nor Haniza Sarmin,
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Abstract |
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The concept of probabilistic splicing system was introduced as a model for stochastic processes using DNA computing
techniques. In this paper we introduce splicing systems endowed with different continuous and discrete probabilistic distributions and
call them as probabilistic splicing systems. We show that any continuous distribution does not increase the generative capacity of
the probabilistic splicing systems with finite components, meanwhile, some discrete distributions increase their generative capacity
up to context-sensitive languages. Finally, we associate certain thresholds with probabilistic splicing systems and this increases the
computational power of splicing systems with finite components. |
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