Biological brains have a natural capacity for resolving certain classification tasks. Studies on
biologically plausible spiking neurons, architectures and mechanisms of artificial neural …

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 …

Nonlinear spiking neural P (NSNP) systems are a class of neural-like computational models
inspired from the nonlinear mechanism of spiking neurons. NSNP systems have a …

Spiking neural P (SNP) systems are a class of neural-like membrane computing models that
are abstracted by applying the mechanisms of spiking neurons. In SNP systems, each …

Nonlinear spiking neural P (NSNP) systems are distributed parallel neural-like computing
models that abstract the nonlinear spiking mechanisms of biological neurons. Echo state …

Abstract The model of Spiking Neural P systems (SNP systems) is a widespread
computational model in the area of membrane computing. It has numerous applications …

Abstract Spiking Neural P (SN P) systems are membrane computing systems that are
abstracted from the behavior of spiking neurons, or brain cells. These systems take …

Under the active area of membrane computing, Spiking Neural P systems (SN P systems)
are models of computations which take inspirations from biological neurons, eg by the …

Spiking neural P systems (SN P systems) are a class of neuron-inspired computation
models, where each synapse independently passes a spike produced by the pre-synaptic …

Structural and behavioural properties of models are very important in development of
complex systems and applications. In this paper, we investigate such properties for some …