The generative capacity of probabilistic splicing systems
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 s...
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iium-420512016-04-01T13:09:07Z http://irep.iium.edu.my/42051/ The generative capacity of probabilistic splicing systems Selvarajoo, Mathuri Turaev, Sherzod Fong, Wan Heng Sarmin, Nor Haniza QA Mathematics QA75 Electronic computers. Computer science 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. Natural Publishing 2015-05 Article PeerReviewed application/pdf en http://irep.iium.edu.my/42051/1/046_The_Generative_Capacity_of_Probabilistic_Splicing_Systems_%289-3_pp_1191-1198_2015%29.pdf Selvarajoo, Mathuri and Turaev, Sherzod and Fong, Wan Heng and Sarmin, Nor Haniza (2015) The generative capacity of probabilistic splicing systems. Applied Mathematics & Information Sciences, 9 (3). pp. 1191-1198. ISSN 1935-0090 http://dx.doi.org/10.12785/amis/090311 |
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English |
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QA Mathematics QA75 Electronic computers. Computer science |
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QA Mathematics QA75 Electronic computers. Computer science Selvarajoo, Mathuri Turaev, Sherzod Fong, Wan Heng Sarmin, Nor Haniza The generative capacity of probabilistic splicing systems |
description |
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. |
format |
Article |
author |
Selvarajoo, Mathuri Turaev, Sherzod Fong, Wan Heng Sarmin, Nor Haniza |
author_facet |
Selvarajoo, Mathuri Turaev, Sherzod Fong, Wan Heng Sarmin, Nor Haniza |
author_sort |
Selvarajoo, Mathuri |
title |
The generative capacity of probabilistic splicing systems |
title_short |
The generative capacity of probabilistic splicing systems |
title_full |
The generative capacity of probabilistic splicing systems |
title_fullStr |
The generative capacity of probabilistic splicing systems |
title_full_unstemmed |
The generative capacity of probabilistic splicing systems |
title_sort |
generative capacity of probabilistic splicing systems |
publisher |
Natural Publishing |
publishDate |
2015 |
url |
http://irep.iium.edu.my/42051/ http://irep.iium.edu.my/42051/ http://irep.iium.edu.my/42051/1/046_The_Generative_Capacity_of_Probabilistic_Splicing_Systems_%289-3_pp_1191-1198_2015%29.pdf |
first_indexed |
2023-09-18T21:00:01Z |
last_indexed |
2023-09-18T21:00:01Z |
_version_ |
1777410561082916864 |