scholarly journals Fraction Reduction in Membrane Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-10
Author(s):  
Ping Guo ◽  
Hong Zhang ◽  
Haizhu Chen ◽  
Ran Liu
Keyword(s):  
Membrane Structure ◽  
Rational Numbers ◽  
P Systems ◽  
P System ◽  
Membrane Systems ◽  
Computing Model ◽  
Rational Computation

Fraction reduction is a basic computation for rational numbers. P system is a new computing model, while the current methods for fraction reductions are not available in these systems. In this paper, we propose a method of fraction reduction and discuss how to carry it out in cell-like P systems with the membrane structure and the rules with priority designed. During the application of fraction reduction rules, synchronization is guaranteed by arranging some special objects in these rules. Our work contributes to performing the rational computation in P systems since the rational operands can be given in the form of fraction.

FURTHER RESULTS ON TIME-FREE P SYSTEMS

2006 ◽  
Vol 17 (01) ◽  
pp. 69-89 ◽  
Author(s):  
MATTEO CAVALIERE ◽  
VINCENZO DEUFEMIA
Keyword(s):  
Parallel Computing ◽  
Chemical Reactions ◽  
Living Cells ◽  
P Systems ◽  
P System ◽  
Membrane Systems ◽  
Open Problems ◽  
Free Evolution ◽  
Cooperative Evolution ◽  
Weight One

Membrane systems (currently called P systems) are parallel computing devices inspired by the structure and the functioning of living cells. A standard feature of P systems is that each rule is executed in exactly one time unit. Actually, in living cells different chemical reactions might take different times to be executed; moreover, it might be hard to know precisely such time of execution. For this reason, in [7] two models of P systems (time-free and clock-free P systems) have been defined and investigated, where the time of execution of the rules is arbitrary and the output produced by the system is always the same, independently of this time. Preliminary results concerning time-free and clock-free P system have been obtained in [6, 7, 8]. In this paper we continue these investigations by considering different combinations of possible ingredients. In particular, we present the universality of time-free P systems using bi-stable catalysts. Then, we prove that this result implies that is not possible to decide whether an arbitrary bi-stable catalytic P system is time-free. We present several results about time-free evolution-communication P systems, where the computation is a mixed application of evolution and symport/antiport rules. In this case we obtain the universality even by using non-cooperative evolution rules and antiports of weight one. Finally, we formulate several open problems.

scholarly journals Variants of derivation modes for which catalytic P systems with one catalyst are computationally complete

2021 ◽  
Author(s):  
Artiom Alhazov ◽  
Rudolf Freund ◽  
Sergiu Ivanov ◽  
Sergey Verlan
Keyword(s):  
Computational Complexity ◽  
P Systems ◽  
P System ◽  
Membrane Systems ◽  
Energy Control ◽  
Computational Completeness ◽  
Current Configuration ◽  
Recursively Enumerable ◽  
Completeness Result ◽  
Recursively Enumerable Sets

AbstractCatalytic P systems are among the first variants of membrane systems ever considered in this area. This variant of systems also features some prominent computational complexity questions, and in particular the problem of using only one catalyst: is one catalyst enough to allow for generating all recursively enumerable sets of multisets? Several additional ingredients have been shown to be sufficient for obtaining even computational completeness with only one catalyst. Last year we could show that the derivation mode $$max_{objects}$$ m a x objects , where we only take those multisets of rules which affect the maximal number of objects in the underlying configuration one catalyst is sufficient for obtaining computational completeness without any other ingredients. In this paper we follow this way of research and show that one catalyst is also sufficient for obtaining computational completeness when using specific variants of derivation modes based on non-extendable multisets of rules: we only take those non-extendable multisets whose application yields the maximal number of generated objects or else those non-extendable multisets whose application yields the maximal difference in the number of objects between the newly generated configuration and the current configuration. A similar computational completeness result can even be obtained when omitting the condition of non-extendability of the applied multisets when taking the maximal difference of objects or the maximal number of generated objects. Moreover, we reconsider simple P system with energy control—both symbol and rule energy-controlled P systems equipped with these new variants of derivation modes yield computational completeness.

scholarly journals An Adaptive Optimization Spiking Neural P System for Binary Problems

2020 ◽  
Vol 31 (01) ◽  
pp. 2050054 ◽  
Author(s):  
Ming Zhu ◽  
Qiang Yang ◽  
Jianping Dong ◽  
Gexiang Zhang ◽  
Xiantai Gou ◽  
...  
Keyword(s):  
Knapsack Problem ◽  
Membrane Computing ◽  
Combinatorial Problems ◽  
P Systems ◽  
P System ◽  
Adaptive Optimization ◽  
Spiking Neural P System ◽  
Multiple Faults ◽  
Computing Model ◽  
Bus System

Optimization Spiking Neural P System (OSNPS) is the first membrane computing model to directly derive an approximate solution of combinatorial problems with a specific reference to the 0/1 knapsack problem. OSNPS is composed of a family of parallel Spiking Neural P Systems (SNPS) that generate candidate solutions of the binary combinatorial problem and a Guider algorithm that adjusts the spiking probabilities of the neurons of the P systems. Although OSNPS is a pioneering structure in membrane computing optimization, its performance is competitive with that of modern and sophisticated metaheuristics for the knapsack problem only in low dimensional cases. In order to overcome the limitations of OSNPS, this paper proposes a novel Dynamic Guider algorithm which employs an adaptive learning and a diversity-based adaptation to control its moving operators. The resulting novel membrane computing model for optimization is here named Adaptive Optimization Spiking Neural P System (AOSNPS). Numerical result shows that the proposed approach is effective to solve the 0/1 knapsack problems and outperforms multiple various algorithms proposed in the literature to solve the same class of problems even for a large number of items (high dimensionality). Furthermore, case studies show that a AOSNPS is effective in fault sections estimation of power systems in different types of fault cases: including a single fault, multiple faults and multiple faults with incomplete and uncertain information in the IEEE 39 bus system and IEEE 118 bus system.

Generation of cycle picture languages using sequential spiking neural P system

2020 ◽  
pp. 583-590
Author(s):  
C. Y. Preethi ◽  
H. A. Christinal ◽  
S. Jebasingh ◽  
D. A. Chandy
Keyword(s):  
Boolean Functions ◽  
Theoretical Study ◽  
P Systems ◽  
P System ◽  
Spiking Neural P System ◽  
Spiking Neural P Systems ◽  
Chain Code ◽  
Computing Model ◽  
Processing Information ◽  
Picture Languages

Spiking Neural P Systems (SN P Systems) is a bio-inspired computing model, abstracting the model of brain in processing information using spikes and neurons. The theoretical study of the model has proved that it can compute sets of positive numbers, Boolean functions and string languages. Cycle picture language is a set of pictures obtained using cycle grammar and chain code representation. In this paper we aim to compute the cycle picture languages using a variant of SN P system namely, Sequential SN P System using neurons and spiking rules. We compute the cycle picture language of sequence of chains.

Arithmetic Expression Evaluation in Membrane Computing with Priority

2011 ◽  
Vol 225-226 ◽  
pp. 1115-1119 ◽  
Author(s):  
Ping Guo ◽  
Sheng Jiao Liu
Keyword(s):  
Membrane Structure ◽  
Membrane Computing ◽  
Arithmetic Operation ◽  
P System ◽  
Arithmetic Expression ◽  
Computing Model ◽  
Model Based ◽  
Operation Rules ◽  
Expression Evaluation

Arithmetic operation and arithmetic expression evaluation are basic operations of a computing model. Based on the rules with priority, this paper discusses arithmetic operation and arithmetic expression evaluation in transition P system. We present the rules of arithmetic operation and the arithmetic of constructing arithmetic expression evaluation’s membrane structure based on the arithmetic operation rules. In the arithmetic operation rules, we use some specifically symbols to make rules applied in a maximally parallel manner, and also assure synchronization need during the rules application.

An Improved Quantum-Inspired Evolutionary Algorithm Based on P Systems with a Dynamic Membrane Structure for Knapsack Problems

2012 ◽  
Vol 239-240 ◽  
pp. 1528-1531 ◽  
Author(s):  
Xue Bai Zhang ◽  
Ge Xiang Zhang ◽  
Ji Xiang Cheng
Keyword(s):  
Evolutionary Algorithms ◽  
Evolutionary Algorithm ◽  
Membrane Structure ◽  
Population Diversity ◽  
P Systems ◽  
Knapsack Problems ◽  
P System ◽  
Dynamic Adjustment ◽  
Dynamic Membrane ◽  
Elementary Membrane

To improve the performance of Quantum-inspired Evolutionary algorithm based on P Systems (QEPS), this paper presents an improved QEPS with a Dynamic Membrane Structure (QEPS-DMS) to solve knapsack problems. QEPS-DMS combines quantum-inspired evolutionary algorithms (QIEAs) with a P system with a dynamic membrane structure. In QEPS-DMS, a QIEA is considered as a subalgorithm to put inside each elementary membrane of a one-level membrane structure, which is dynamically adjusted in the process of evolution by applying a criterion for measuring population diversity. The dynamic adjustment includes the processes of membrane dissolution and creation. Knapsack problems are applied to test the effectiveness of QEPS-DMS. Experimental results show that QEPS-DMS outperforms QEPS and three variants of QIEAs recently reported in the literature.

Bimolecular and Monomolecular Lipid Films: Selected Area Electron Diffraction

1969 ◽  
Vol 27 ◽  
pp. 338-339
Author(s):  
Robert M. Glaeser ◽  
David W. Deamer
Keyword(s):  
Electron Diffraction ◽  
Membrane Structure ◽  
Molecular Organization ◽  
Membrane Material ◽  
X Ray Diffraction ◽  
Membrane Systems ◽  
X Ray ◽  
Selected Area Electron Diffraction ◽  
Lipid Films ◽  
Ultimate Objective

In the investigation of the molecular organization of cell membranes it is often supposed that lipid molecules are arranged in a bimolecular film. X-ray diffraction data obtained in a direction perpendicular to the plane of suitably layered membrane systems have generally been interpreted in accord with such a model of the membrane structure. The present studies were begun in order to determine whether selected area electron diffraction would provide a tool of sufficient sensitivity to permit investigation of the degree of intermolecular order within lipid films. The ultimate objective would then be to apply the method to single fragments of cell membrane material in order to obtain data complementary to the transverse data obtainable by x-ray diffraction.

scholarly journals When catalytic P systems with one catalyst can be computationally complete

2021 ◽  
Author(s):  
Artiom Alhazov ◽  
Rudolf Freund ◽  
Sergiu Ivanov
Keyword(s):  
Computational Complexity ◽  
P Systems ◽  
Membrane Systems ◽  
Computational Completeness ◽  
Recursively Enumerable ◽  
Recursively Enumerable Sets

AbstractCatalytic P systems are among the first variants of membrane systems ever considered in this area. This variant of systems also features some prominent computational complexity questions, and in particular the problem of using only one catalyst in the whole system: is one catalyst enough to allow for generating all recursively enumerable sets of multisets? Several additional ingredients have been shown to be sufficient for obtaining computational completeness even with only one catalyst. In this paper, we show that one catalyst is sufficient for obtaining computational completeness if either catalytic rules have weak priority over non-catalytic rules or else instead of the standard maximally parallel derivation mode, we use the derivation mode maxobjects, i.e., we only take those multisets of rules which affect the maximal number of objects in the underlying configuration.

scholarly journals Novel Numerical Spiking Neural P Systems with a Variable Consumption Strategy

Processes ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 549
Author(s):  
Xiu Yin ◽  
Xiyu Liu ◽  
Minghe Sun ◽  
Qianqian Ren
Keyword(s):  
Production Functions ◽  
P Systems ◽  
P System ◽  
Computing Device ◽  
Spiking Neural P Systems ◽  
Distributed Parallel Computing ◽  
Production Values ◽  
Novel Variant ◽  
Turing Universality ◽  
Variable Consumption

A novel variant of NSN P systems, called numerical spiking neural P systems with a variable consumption strategy (NSNVC P systems), is proposed. Like the spiking rules consuming spikes in spiking neural P systems, NSNVC P systems introduce a variable consumption strategy by modifying the form of the production functions used in NSN P systems. Similar to the delay feature of the spiking rules, NSNVC P systems introduce a postponement feature into the production functions. The execution of the production functions in NSNVC P systems is controlled by two, i.e., polarization and threshold, conditions. Multiple synaptic channels are used to transmit the charges and the production values in NSNVC P systems. The proposed NSNVC P systems are a type of distributed parallel computing models with a directed graphical structure. The Turing universality of the proposed NSNVC P systems is proved as number generating/accepting devices. Detailed descriptions are provided for NSNVC P systems as number generating/accepting devices. In addition, a universal NSNVC P system with 66 neurons is constructed as a function computing device.

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