In this paper, we create a matrix representation for spiking neural P systems with structural
plasticity (SNPSP, for short), taking inspiration from existing algorithms and representations …

The utilization of a parallel processor such as the graphics processing unit (GPU) is only
natural for the simulation of spiking neural P systems (SN P systems) because of their …

In the 2010, matrix representation of SN P system without delay was presented while in the
case of SN P systems with delay, matrix representation was suggested in the 2017. These …

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 …

Spiking neural P systems (SNP systems) are parallel and non-deterministic models of
computation, inspired by the neural system of the brain. A variant of SNP systems known as …

Spiking Neural P system is a computing model inspired on how the neurons in a living being
are interconnected and exchange information. As a model in embrane computing, it is a non …

To date, parallel simulation algorithms for spiking neural P (SNP) systems are based on a
matrix representation. This way, the simulation is implemented with linear algebra …

P systems were introduced more than two decades ago by Gheorghe Pǎun. They are known
as nondeterministic maximally parallel computing models. Most of their variants are proved …

Spiking Neural P systems (in short, SNP systems) are computing models based on living
neurons. SNP systems are non-deterministic and parallel, hence making use of a parallel …

Spiking neural P (SN P) systems are models of computation inspired by spiking neurons and
part of the third generation of neuron models. SN P systems are equivalent to Turing …