Abstract
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.
Original language | English |
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Pages (from-to) | 1191-1198 |
Number of pages | 8 |
Journal | Applied Mathematics and Information Sciences |
Volume | 9 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Keywords
- DNA computing
- Generative capacity
- Probabilistic splicing systems
- Splicing systems
ASJC Scopus subject areas
- Analysis
- Numerical Analysis
- Computer Science Applications
- Computational Theory and Mathematics
- Applied Mathematics