IEEE Transactions on NanoBioscience · 2015 · 68 citations · 31 references
ComputingComputer ScienceMathematicsComputational NeuroscienceNeural EngineeringSet TheoryNeural NetworksSpiking Neural NetworksTuring MachinesCatastrophic ForgettingComputable NumbersLinear SetsNeural Dynamical SystemsSpiking ActivitySpiking Neural Network ModelsSpiking Neuron Models
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.
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Computation: Finite and Infinite Machines.
D. A. Clarke, Marvin Minsky · American Mathematical Monthly · 1968 · 2.6K citations
Mihai Ionescu, Gheorghe Pǎun, Takashi Yokomori · Fundamenta Informaticae · 2006 · 767 citations
Life Sciences, Computer Science, Computational Neuroscience +11