Foreword

Guest Editors: Marian Gheorghe, Gheorghe Păun, Gexiang Zhang
Foreword – Special Issue on Membrane Computing
pp. 3–4
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Keqin JIANG, Yufang HUANG, Jinbang XU, Zhihua CHEN
Small universal sequential spiking neural P systems based on minimum spike number
pp. 5–18

 

Abstract. Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. Recently, a variant of SN P systems was considered: at each step the neuron with the minimum number of spikes among the neurons that can spike will fire. It has been shown, in previous papers, that such systems are Turing complete when the computing result is obtained by accumulating the spikes in the output neuron. In this work, we use a natural way to define the computing result of the systems, by considering the time interval between the first two spikes emitted by the output neuron. As devices for computing functions, we construct a universal sequential SN P system based on minimum spike number (without delay) which uses 137 neurons; as a generator of sets of numbers, a universal sequential SN P system based on minimum spike number (without delay) with 126 neurons is also obtained. Read the pdf

 

 

 

 

 

 

 

 

 

 

 

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Yuan KONG, Keqin JIANG, Zhihua CHEN, Jinbang XU
Small Universal Spiking Neural P Systems with Astrocytes
pp. 19–32

 

Abstract. Spiking neural P systems with astrocytes (SNPA systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes, where also astrocytes are considered, having an excitatory or an inhibitory influence on synapses. Looking for small universal computing devices is a classical research topic in computer science. In this work, we investigate small universal SNPA systems as both devices computing functions and devices generating sets of numbers. Specifically, as devices of computing functions, a universal SNPA system (without delay and forgetting rules) using 57 neurons and 19 astrocytes is obtained; as generators of sets of numbers, a universal SNPA system (without delay and forgetting rules) using 54 neurons and 17 astrocytes is found. These improve previous results on SN P systems without astrocytes and show the role of these features. Read the pdf.

 

 

 

 

 

 

 

 

 

 

 

 

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Venkata Padmavati METTA, Kamala KRITHIVASAN
Parallel Programming in Spiking Neural P Systems with Anti-Spikes
pp. 33–45

 

Abstract. In spiking neural P systems with anti-spikes, integers can be represented as the number of spikes/anti-spikes present in a neuron. Thus it is possible to represent increment, decrement, relational operations and assignment statements using spiking neural P systems. With these basic structures, it is also possible to represent programming language constructs like conditional, iterative and different types of execution constructs. In this paper we consider a general-purpose parallel programming language that handles integer variables and is implemented using spiking neural P systems with anti-spikes. Read the pdf

 

 

 

 

 

 

 

 

 

 

 

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Radu NICOLESCU, Huiling WU
Complex Objects for Complex Applications
pp. 46–62

 

Abstract. We further develop our earlier Prolog-like complex objects proposal and present several new and improved solutions, for a variety of problems: a faster SAT solution with a fixed number of rules and a set of transformations and components that can build a termination detection algorithm. These results enforce our conjecture that our complex object proposals enable an efficient high-level programming style for P systems. Read the pdf

 

 

 

 

 

 

 

 

 

 

 

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Hong PENG, Yufan YANG, Jiarong ZHANG, Xiaoli HUANG, Jun WANG
A Region-based Color Image Segmentation Method Based on P Systems
pp. 63–75

 

Abstract. Region growing-based color image segmentation approaches suffer from expensive computation cost. In order to overcome this issue, a novel region-based color image segmentation method based on P systems is proposed in this paper. A tissue-like P system is designed in such a way that an adaptive selection of target regions is achieved. The proposed method is evaluated on several real-life color images. Read the pdf

 

 

 

 

 

 

 

 

 

 

 

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Hong PENG, Jiarong ZHANG, Yang JIANG, Xiaoli HUANG, Jun WANG
DE-MC: A Membrane Clustering Algorithm Based on Differential Evolution Mechanism
pp. 76–88

 

Abstract. A clustering algorithm using the framework of membrane computing is proposed in this paper. The P system used is a cell-like P system of two-layer nested structure: a skin membrane contains several elementary membranes. Each object in elementary membranes represents a group of cluster centers. Objects in the system evolve by using the differential evolution mechanism, and then the global optimal object in the skin membrane is updated by the best objects in all elementary membranes. The cell-like P system can automatically find the best cluster centers for a data set. The proposed DE-MC algorithm is evaluated on an artificial data set and a real-life data set and is further compared with classical k-means algorithm, GA-based clustering algorithm and DE-based clustering algorithm, respectively. The comparison results reveal that the proposed DE-MC algorithm is superior to the other three clustering algorithms in terms of clustering quality and robustness. Read the pdf

 

 

 

 

 

 

 

 

 

 

 

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Ignacio PÉREZ–HURTADO, Luis VALENCIA–CABRERA, José M. CHACÓN, Agustin RISCOS–NÚÑEZ, Mario J. PÉREZ–JIMÉNEZ
A P–Lingua based Simulator for Tissue P Systems with Cell Separation
pp. 89–102

 

Abstract. Tissue P systems are one of the currently active research topics within the field of Membrane Computing. In particular, their computational efficiency is being investigated in the case when the number of cells can grow by means of cell separation rules. In order to complement this study, it is useful to provide simulation software tools for this variant of tissue P systems.
The paper presents an extension of P-Lingua specification language, in order to include the class of tissue P systems with cell separation. This extension involves updating the P-Lingua parser, by reinterpreting some operators, along with some new ingredients. In addition, a new built-in simulation algorithm that has been added to the core library of P-Lingua is also presented.
A case study of a family of tissue P systems with cell separation of type TSC(3) solving SAT is used to show the dynamics of the simulator. Read the pdf

 

 

 

 

 

 

 

 

 

 

 

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K.G. SUBRAMANIAN, Pradeep ISAWASAN, Ibrahim VENKAT, Linqiang PAN
Parallel Array-rewriting P Systems
pp. 103–116

 

Abstract. A variant of array-rewriting P systems that uses parallel rewriting of arrays in the regions is introduced. The generative power of this model is compared with certain array grammars generating array languages. It is shown that geometric arrays such as hollow rectangles and hollow squares can be generated by parallel array P systems with a priority relation on the rules. The advantage of the proposed variant is that the number of membranes necessary for generating certain array language is reduced in the constructions as array generation devices. Read the pdf