Solving subset sum by spiking neural P systems with astrocytes producing calcium

Aman, Bogdan

doi:10.1007/s11047-022-09900-7

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…SN P systems with delays on synapses were proposed by considering the length of axons [14], where postsynaptic neurons get spikes at different times. By introducing astrocytes, a kind of special cell in neuron systems, the spike transmission in synapses can be controlled [15] [16], and SN P systems with weights have been proposed for multiple connections between two neurons, [17] [18]. We use the weight w to denote w synapses between neurons.…”

Section: E a A D mentioning

confidence: 99%

On the Universality of Spiking Neural P Systems With Multiple Channels and Autapses

Ning,

Yang,

Sun

et al. 2024

IEEE Access

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Spiking neural P systems (SN P systems) abstract the structure and function of neurons and nervous systems. By adopting some biological observations or mathematical considerations in SN P systems, many variants have been proposed. In this work, through combining two interesting variants, SN P systems with multiple channels (SNP-MC systems) and SN P systems with autapses (SNP-AU systems), we propose SN P systems with multiple channels and autapses (SNP-MCA systems) and research their universality. SNP-MCA systems are proved to be universal in the generation of numbers. For computing functions, a universal SNP-MCA system with 25 neurons is constructed, which requires fewer neurons than the two variants.

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Section: E a A D mentioning

confidence: 99%

On the Universality of Spiking Neural P Systems With Multiple Channels and Autapses

Ning,

Yang,

Sun

et al. 2024

IEEE Access

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“…Furthermore, SNPSs with structural plasticity and time-free SNPS models can solve the SUBSET-SUM problem in a feasible time [16,17]. In [18] it has been proved that SNPS with astrocytes producing calcium can solve the SUBSET-SUM problem in a polynomial time. Recently, a linear time uniform solution for the Boolean SAT problem using self-adapting SNPS with refractory period and propagation delay is derived in [19].…”

Section: Introductionmentioning

confidence: 99%

Solving the SAT problem using spiking neural P systems with coloured spikes and division rules

Peul,

Sosik

2024

Preprint

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Spiking neural P systems (SNPS) are variants of the third-generation neural networks. In the last few decades, different variants of SNPS models have been introduced. In most of the SNPS models, spikes are represented using an alphabet with just one letter. In this paper we use a deterministic SNPS model with coloured spikes (i.e., the alphabet representing spikes contains multiple letters), together with neuron division rules to demonstrate an efficient solution to the SAT problem. As a result, we provide a simpler construction with significantly less class resources to solve the SAT problem in comparison to previously reported results using SNPSs. MSC Classification: 68Q05 , 68Q42 , 68Q45 , 92D20

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Solving subset sum and SAT problems by reaction systems

Aman,

Ciobanu

2024

Nat Comput

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Solving subset sum by spiking neural P systems with astrocytes producing calcium

Cited by 8 publications

References 19 publications

On the Universality of Spiking Neural P Systems With Multiple Channels and Autapses

On the Universality of Spiking Neural P Systems With Multiple Channels and Autapses

Solving the SAT problem using spiking neural P systems with coloured spikes and division rules

Solving subset sum and SAT problems by reaction systems

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