Adenocarcinoma 发表于 2025-3-26 23:33:24
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Computational Power of Symport/Antiport: History, Advances, and Open Problems respect to the development of computational completeness results improving descriptional complexity parameters. We consider the number of membranes (cells in tissue P systems), the weight of the rules, and the number of objects. Then we establish our newest results: P systems with only one membraneoriginality 发表于 2025-3-27 11:14:13
http://reply.papertrans.cn/64/6304/630352/630352_34.png仔细阅读 发表于 2025-3-27 17:38:44
Some Recent Results Concerning Deterministic P Systemsl the rules in a maximally parallel manner: at each step, a maximal multiset of rules are nondeterministically selected and applied in parallel to the current configuration to derive the next configuration (thus, the next configuration is not unique, in general). The system is deterministic if at eagiggle 发表于 2025-3-27 17:53:37
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On Evolutionary Lineages of Membrane Systemsorresponds to that of a finite transducer. An important characteristics of the model is its interactive behavior. Then we study the computational power of evolutionary lineages of such P systems. Referring to known results from the structural complexity theory (Karp and Lipton, Wiedermann and van Leoptic-nerve 发表于 2025-3-28 05:12:50
http://reply.papertrans.cn/64/6304/630352/630352_38.png魅力 发表于 2025-3-28 06:15:46
Symbol/Membrane Complexity of P Systems with Symport/Antiport Rulestiport rules simulating register machines with the number of registers depending on the number . of symbols and the number . of membranes. For instance, any recursively enumerable set of natural numbers can be generated (accepted) by systems with . ≥ 2 symbols and . ≥ 1 membranes such that . + . ≥ 6让空气进入 发表于 2025-3-28 14:09:12
On P Systems as a Modelling Tool for Biological Systemsy corresponding to the kinetic coefficient which, in bio-chemistry, is usually associated to each molecular reaction. The behaviour of these P systems is then defined according to a strategy which, in each step, randomly selects the next rule to be applied depending upon a certain distribution of pr