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On String Languages Generated by Spiking Neural P Systems
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In this paper, the authors consider spiking neural P systems as binary string generators, where the set of spike trains of halting computations of a given system constitutes the language generated by that system.Abstract:
We continue the study of spiking neural P systems by considering these computing devices as binary string generators: the set of spike trains of halting computations of a given system constitutes the language generated by that system. Although the "direct" generative capacity of spiking neural P systems is rather restricted (some very simple languages cannot be generated in this framework), regular languages are inverse-morphic images of languages of finite spiking neural P systems, and recursively enumerable languages are projections of inverse-morphic images of languages generated by spiking neural P systems.read more
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Journal ArticleDOI
On spiking neural P systems
TL;DR: This work deals with several aspects concerning the formal verification of SN P systems and the computing power of some variants, and proposes a methodology based on the information given by the transition diagram associated with an SN P system which establishes the soundness and completeness of the system with respect to the problem it tries to resolve.
Journal ArticleDOI
An optimization spiking neural p system for approximately solving combinatorial optimization problems.
TL;DR: An extended spiking neural P system (ESNPS) has been proposed by introducing the probabilistic selection of evolution rules and multi-neurons output and a family of ESNPS, called optimization spiking Neural P system, are further designed through introducing a guider to adaptively adjust rule probabilities to approximately solve combinatorial optimization problems.
Journal Article
Spiking Neural P Systems: A Tutorial.
TL;DR: A recently initiated branch of membrane computing with motivation from neural computing, with basic ideas, some examples, classes of spiking neural P systems, some results concerning their power, research topics.
Journal ArticleDOI
Asynchronous spiking neural P systems
TL;DR: It is proved that asynchronous systems, with extended rules, and where each neuron is either bounded or unbounded, are not computationally complete and the configuration reachability, membership, emptiness, infiniteness, and disjointness problems are shown to be decidable.
Journal ArticleDOI
Spiking neural P systems with neuron division and budding
TL;DR: The features of neuron division and neuron budding are introduced into the framework of spiking neural P systems, which are processes inspired by neural stem cell division to efficiently solve computationally hard problems by means of a space-time tradeoff.
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.
Book
Computation: Finite and Infinite Machines
TL;DR: In this article, the authors present an abstract theory that categorically and systematically describes what all these machines can do and what they cannot do, giving sound theoretical or practical grounds for each judgment, and the abstract theory tells us in no uncertain terms that the machines' potential range is enormous and that its theoretical limitations are of the subtlest and most elusive sort.
Book
Membrane Computing: An Introduction
TL;DR: This chapter discusses Membrane Computing, What It Is and What It is Not, and attempts to get back to reality with open problems and Universality results.