The present work focuses on three notions about spiking neural P systems (SN P systems),
namely normal forms, homogeneous systems, and software tools for easy access and visual …

Over the years, spiking neural P systems (SNPS) have grown into a popular model in
membrane computing because of their diverse range of applications. In this paper, we give a …

Pulse coupled neural networks (PCNN, for short) are models abstracting the synchronization
behavior observed experimentally for the cortical neurons in the visual cortex of a cat's brain …

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 …

Spiking neural P systems (SN P systems) are bio-inspired neural-like computing models,
which are obtained by abstracting the way of biological neurons' spiking and communication …

Spiking neural P systems (SNP systems, in short) are a class of distributed parallel
computing systems inspired from the neurophysiological behavior of biological spiking …

Axon P systems are computing models with a linear structure in the sense that all nodes (ie,
computing units) are arranged one by one along the axon. Such models have a good …

Spiking neural P systems (SN P systems) are a class of distributed and parallel neural-like
computing models, inspired from the way neurons communicate by means of spikes. In this …

Dynamic threshold neural P (DTNP) systems are a new variant of spiking neural P (SNP)
systems, abstracted by the spiking and dynamic threshold mechanisms of biological …

Spiking neural P (SNP) systems are a class of parallel, distributed, and nondeterministic
computing models inspired by the spiking of biological neurons. In this work, the biological …