Numerical spiking neural P systems with production functions on synapses.

Numerical spiking neural (NSN) P systems are a class of distributed parallel neural computing devices, where the values of numerical variables are used to encode the information, the programs that process the variables are expressed by continuous production functions. In this work, numerical spiking neural P systems with functions on synapses (NSNFS P systems), as a variant of numerical spike neural P systems, are proposed. In NSNFS P systems, continuous production functions are considered at synapses of neurons and used to transmit information between two neurons connected by a synapse. The computation power of NSNFS P systems as a kind of digital generating devices and digital accepting devices is investigated respectively, when the continuous production functions on each synapse are linear and only one numerical variable is involved in each neuron. The results show that numerical spiking neural P systems with production functions on synapses are still universal. • A novel Turing complete paradigm of spiking neural P systems with synapses as computational units. • The Turing completeness of the proposed systems is proved as number generating devices. • The Turing completeness of the proposed systems is proved as number accepting devices. [ABSTRACT FROM AUTHOR]