scholarly journals Spiking Neural P Systems. Recent Results, Research Topics

2009 ◽  
pp. 273-291 ◽  
Author(s):  
Gheorghe Păun ◽  
Mario J. Pérez-Jiménez
Keyword(s):  
P Systems ◽  
Research Topics ◽  
Spiking Neural P Systems

SPIKING NEURAL P SYSTEMS: AN EARLY SURVEY

2007 ◽  
Vol 18 (03) ◽  
pp. 435-455 ◽  
Author(s):  
GHEORGHE PĂUN ◽  
MARIO J. PÉREZ-JIMÉNEZ ◽  
ARTO SALOMAA
Keyword(s):  
Membrane Computing ◽  
Normal Forms ◽  
P Systems ◽  
Research Topics ◽  
Open Problems ◽  
Computing Power ◽  
Spiking Neural P Systems ◽  
A Cell ◽  
Early Survey ◽  
Basic Ideas

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.

Spiking Neural P Systems

2011 ◽  
pp. 60-73 ◽  
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.

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

2013 ◽  
pp. 145-160 ◽  
Author(s):  
Francis George C. Cabarle ◽  
Henry N. Adorna
Keyword(s):  
Petri Nets ◽  
P Systems ◽  
Spiking Neural P Systems ◽  
And Behaviors

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

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

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.

An Adaptive e-Learning Environment Using Distributed Spiking Neural P Systems

2011 ◽  
Author(s):  
Susan Elias ◽  
A. P. Sarath Chandar ◽  
Kamala Krithivasan ◽  
S. V. Raghavan
Keyword(s):  
Learning Environment ◽  
P Systems ◽  
Spiking Neural P Systems ◽  
E Learning

Computational power of sequential spiking neural P systems with multiple channels

2021 ◽  
Author(s):  
Zeqiong Lv ◽  
Qian Yang ◽  
Hong Peng ◽  
Xiaoxiao Song ◽  
Jun Wang
Keyword(s):  
P Systems ◽  
Multiple Channels ◽  
Computational Power ◽  
Spiking Neural P Systems

A Parallel Image Skeletonizing Method Using Spiking Neural P Systems with Weights

2018 ◽  
Vol 50 (2) ◽  
pp. 1485-1502 ◽  
Author(s):  
Tao Song ◽  
Shanchen Pang ◽  
Shaohua Hao ◽  
Alfonso Rodríguez-Patón ◽  
Pan Zheng
Keyword(s):  
P Systems ◽  
Spiking Neural P Systems ◽  
Parallel Image

Small Universal Spiking Neural P Systems with Exhaustive Use of Rules

2010 ◽  
Vol 7 (5) ◽  
pp. 890-899 ◽  
Author(s):  
Xingyi Zhang ◽  
Yun Jiang ◽  
Linqiang Pan
Keyword(s):  
P Systems ◽  
Spiking Neural P Systems
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