Journal
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
Volume 30, Issue 10, Pages -Publisher
WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0129065720500082
Keywords
Membrane computing; spiking neural P systems; nonlinear spiking neural P systems; universality; register machines
Categories
Funding
- National Natural Science Foundation of China [61472328]
- Research Fund of Sichuan Science and Technology Project [2018JY0083]
- Research Foundation of the Education Department of Sichuan province [17TD0034]
- Innovation Fund of Postgraduate, Xihua University, China [YCJJ2019019, YCJJ2019020]
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This paper proposes a new variant of spiking neural P systems (in short, SNP systems), nonlinear spiking neural P systems (in short, NSNP systems). In NSNP systems, the state of each neuron is denoted by a real number, and a real configuration vector is used to characterize the state of the whole system. A new type of spiking rules, nonlinear spiking rules, is introduced to handle the neuron's firing, where the consumed and generated amounts of spikes are often expressed by the nonlinear functions of the state of the neuron. NSNP systems are a class of distributed parallel and nondeterministic computing systems. The computational power of NSNP systems is discussed. Specifically, it is proved that NSNP systems as number-generating/accepting devices are Turing-universal. Moreover, we establish two small universal NSNP systems for function computing and number generator, containing 117 neurons and 164 neurons, respectively.
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