Notes on Spiking Neural P Systems and Finite Automata
|Author||Cabarle, Francis George C.
Adorna, Henry N.
Pérez Jiménez, Mario de Jesús
|Department||Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial|
|Published in||Proceedings of the Thirteenth Brainstorming Week on Membrane Computing, 77-90. Sevilla, E.T.S. de Ingeniería Informática, 2-6 de Febrero, 2015,|
|Abstract||Spiking neural P systems (in short, SNP systems) are membrane computing
models inspired by the pulse coding of information in biological neurons. SNP systems
with standard rules have neurons that emit at most one spike ...
Spiking neural P systems (in short, SNP systems) are membrane computing models inspired by the pulse coding of information in biological neurons. SNP systems with standard rules have neurons that emit at most one spike (the pulse) each step, and have either an input or output neuron connected to the environment. SNP transducers were introduced, where both input and output neurons were used. More recently, SNP modules were introduced which generalize SNP transducers: extended rules are used (more than one spike can be emitted each step) and a set of input and output neurons can be used. In this work we continue relating SNP modules and nite automata: (i) we amend previous constructions for DFA and DFST simulations, (ii) improve the construction from three neurons down to one neuron, (iii) DFA with output are simulated, and (iv) we generate automatic sequences using results from.