Spiking neural P systems with weights and delays on synapses

Spiking neural P systems (SN P systems) are bio-inspired neural-like computational devices that mimic the communication between two nearby neurons and the spike changes in the neuron. This study incorporates concepts of the weight of synapses and the delay on synapses to increase the bio-explainability (the model can better simulate the communication between neurons), where the weight is a natural feature of synapses, and the delay is that in the communication between neurons, through synapses. Thus, an innovative type of spiking neural-like P system is defined, called spiking neural P systems with weights and delays on synapses (WDSN P systems). In WDSN P systems, synapses are assigned weights and delays, where weights are real numbers and delays are natural numbers. Results proved in this paper show that WDSN P systems can reach Turing universality in the generating and accepting mode. The semi-uniform solution for the Subset Sum problem demonstrates that WDSN P systems can solve NP-complete problems efficiently.