Matrix representation and simulation algorithm of numerical spiking neural P systems

Spiking neural P systems (SNP systems) are biologically inspired models of computation based on the firing behavior of neurons. Variations of these systems have been proposed to solve more specific problems. A more recent variation called the numerical spiking neural P systems combines concepts from SNP systems and numerical P systems to create a new model of computation. This model allows continuous production functions and, in effect, allows for faster computation. In this work, we propose a matrix representation and a corresponding simulation algorithm for NSNP systems. Having a matrix representation and a simulation algorithm allows for testing of solutions in silico. We also present an NSNP system that solves the subset sum problem, and use the matrix representation and simulation algorithm to obtain the solution.