Spiking Neural P Systems. Recent Results, Research Topics

Spiking neural P systems were introduced in the end of the year 2005, in the aim of incorporating in membrane computing the idea of working with unique objects ("spikes"), encoding the information in the time elapsed between consecutive spikes sent from a cell/neuron to another cell/neuron. More than one dozen of papers where written in the meantime, clarifying many of the basic properties of these devices, especially related to their computing power. The present paper quickly surveys the basic ideas and the basic results, presenting a complete to-date bibliography, and also giving a completing result related to the normal forms possible for spiking neural P systems: we prove that the indegree of such systems (the maximal number of incoming synapses of neurons) can be bounded by 2 without losing the computational completeness. A series of research topics and open problems are formulated.

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Spiking Neural P Systems

Advancing Artificial Intelligence through Biological Process Applications ◽

10.4018/978-1-59904-996-0.ch004 ◽

2011 ◽

pp. 60-73 ◽

Cited By ~ 4

Author(s):

Gheorghe Paun ◽

Mario J. Perez-Jimenez

Keyword(s):

Computational Complexity ◽

Membrane Computing ◽

Research Area ◽

P Systems ◽

Neural Computing ◽

Research Topics ◽

Computing Power ◽

Spiking Neural P Systems ◽

Basic Ideas ◽

Source Of Information

This chapter is a quick survey of spiking neural P systems, a branch of membrane computing which was recently introduced with motivation from neural computing based on spiking. Basic ideas, examples, some results (especially concerning the computing power and the computational complexity/efficiency), and several research topics are discussed. The presentation is succinct and informal, meant mainly to let the reader having a flavour of this research area. The additional references are an important source of information in this respect.

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Spiking Neural P Systems - A Quick Survey and Some Research Topics

2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing ◽

10.1109/synasc.2014.11 ◽

2014 ◽

Author(s):

Gheorghe Paun

Keyword(s):

P Systems ◽

Research Topics ◽

Spiking Neural P Systems

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On Structures and Behaviors of Spiking Neural P Systems and Petri Nets

Membrane Computing - Lecture Notes in Computer Science ◽

10.1007/978-3-642-36751-9_11 ◽

2013 ◽

pp. 145-160 ◽

Cited By ~ 6

Author(s):

Francis George C. Cabarle ◽

Henry N. Adorna

Keyword(s):

Petri Nets ◽

P Systems ◽

Spiking Neural P Systems ◽

And Behaviors

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Small universal spiking neural P systems with dendritic/axonal delays and dendritic trunk/feedback

Neural Networks ◽

10.1016/j.neunet.2021.02.010 ◽

2021 ◽

Vol 138 ◽

pp. 126-139

Author(s):

Luis Garcia ◽

Giovanny Sanchez ◽

Eduardo Vazquez ◽

Gerardo Avalos ◽

Esteban Anides ◽

...

Keyword(s):

P Systems ◽

Spiking Neural P Systems

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Novel Numerical Spiking Neural P Systems with a Variable Consumption Strategy

Processes ◽

10.3390/pr9030549 ◽

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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