Journal ArticleDOI
On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses
Tao Song,Jinbang Xu,Linqiang Pan +2 more
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TLDR
A Turing universal spiking neural P system with rules on synapses having 6 neurons is constructed, which can generate any set of Turing computable natural numbers.Abstract:
Spiking neural P systems with rules on synapses are a new variant of spiking neural P systems. In the systems, the neuron contains only spikes, while the spiking/forgetting rules are moved on the synapses. It was obtained that such system with 30 neurons (using extended spiking rules) or with 39 neurons (using standard spiking rules) is Turing universal. In this work, this number is improved to 6. Specifically, we construct a Turing universal spiking neural P system with rules on synapses having 6 neurons, which can generate any set of Turing computable natural numbers. As well, it is obtained that spiking neural P system with rules on synapses having less than two neurons are not Turing universal: i) such systems having one neuron can characterize the family of finite sets of natural numbers; ii) the family of sets of numbers generated by the systems having two neurons is included in the family of semi-linear sets of natural numbers.read more
Citations
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Journal ArticleDOI
A computational approach for nuclear export signals identification using spiking neural P systems
TL;DR: This work endeavors to tackle the challenge by proposing a computational approach to identifying nuclear export signal using spiking neural P (SN P) systems, and is the first feasible attempt to use SN P systems in computational biology after many theoretical advancements.
Journal ArticleDOI
An improved gravitational search algorithm for green partner selection in virtual enterprises
TL;DR: An improved algorithm I-GSA/PSO that combines gravitational search algorithm and particle swarm optimization is developed to solve G-PSP in virtual enterprises and shows that it is effective and outperforms other evolutionary algorithms in solving G- PSP.
Journal ArticleDOI
A small universal spiking neural P system with communication on request
TL;DR: Here, a Turing universal SNQ P system is constructed with only 14 neurons, which answers an open problem whether the number of neurons for constructing a Turinguniversal SN Q P system can be further improved.
Book ChapterDOI
Spiking Neural P Systems: Theoretical Results and Applications
TL;DR: The formal definition of standard SN P systems is introduced and some notions which are often used in this field are introduced, and the theoretical results about the computation power and efficiency ofSN P systems are surveyed.
Journal ArticleDOI
Numerical P systems with production thresholds
TL;DR: It is proved that NP systems with lower-thresholds (the production function value can be distributed only when it is not smaller than a given constant), with one membrane working both in the all-parallel mode and in the sequential mode, are universal.
References
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Book
Spiking Neuron Models: Single Neurons, Populations, Plasticity
TL;DR: A comparison of single and two-dimensional neuron models for spiking neuron models and models of Synaptic Plasticity shows that the former are superior to the latter, while the latter are better suited to population models.
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Journal ArticleDOI
Networks of spiking neurons: the third generation of neural network models
TL;DR: It is shown that networks of spiking neurons are, with regard to the number of neurons that are needed, computationally more powerful than other neural network models based on McCulloch Pitts neurons and sigmoidal gates.
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The Oxford Handbook of Membrane Computing
TL;DR: This handbook provides both a comprehensive survey of available knowledge and established research topics, and a guide to recent developments in the field, covering the subject from theory to applications.
Journal ArticleDOI
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TL;DR: A state-of-the-art review of the development of spiking neurons and SNNs is presented, and insight into their evolution as the third generation neural networks is provided.