Small universal Turing machines
Theoretical Computer Science - Special issue on universal machines and computations
Small universal register machines
Theoretical Computer Science - Special issue on universal machines and computations
Handbook of formal languages, vol. 3: beyond words
Handbook of formal languages, vol. 3: beyond words
Pulsed Neural Networks
Membrane Computing: An Introduction
Membrane Computing: An Introduction
Spiking Neuron Models: An Introduction
Spiking Neuron Models: An Introduction
Computation: finite and infinite machines
Computation: finite and infinite machines
Fundamenta Informaticae
Normal forms for spiking neural P systems
Theoretical Computer Science
On String Languages Generated by Spiking Neural P Systems
Fundamenta Informaticae - New Frontiers in Scientific Discovery - Commemorating the Life and Work of Zdzislaw Pawlak
Spiking neural P systems with extended rules: universality and languages
Natural Computing: an international journal
Smaller Universal Spiking Neural P Systems
Fundamenta Informaticae
Asynchronous spiking neural P systems: decidability and undecidability
DNA13'07 Proceedings of the 13th international conference on DNA computing
Characterizations of some restricted spiking neural p systems
WMC'06 Proceedings of the 7th international conference on Membrane Computing
Spiking Neural P Systems with Weighted Synapses
Neural Processing Letters
Computationally complete spiking neural P systems without delay: two types of neurons are enough
CMC'10 Proceedings of the 11th international conference on Membrane computing
Time-free spiking neural p systems
Neural Computation
Limited Asynchronous Spiking Neural P Systems
Fundamenta Informaticae - Theory that Counts: To Oscar Ibarra on His 70th Birthday
Reversible spiking neural P systems
Frontiers of Computer Science: Selected Publications from Chinese Universities
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Spiking neural P systems are a class of distributed parallel computing models inspired from the way the neurons communicate with each other by means of electrical impulses (called "spikes"). In this paper, we consider a restricted variant of spiking neural P systems, called homogeneous spiking neural P systems, where each neuron has the same set of rules. The universality of homogeneous spiking neural P systems is investigated. One of universality results is that it is sufficient for homogeneous spiking neural P system to have only one neuron that behaves nondeterministically in order to achieve Turing completeness.