Spiking neural P systems: main ideas and results
Alberto Leporati, Giancarlo Mauri, Claudio Zandron
Abstract
Abstract Spiking neural P systems are parallel and distributed computation devices which are inspired by the neuro-physiological behavior of biological neurons. In this paper we will present, with a tutorial approach, the main underlying ideas and the most interesting variants that have been proposed in the literature. In particular, we will discuss the results on the computational power of these models, both in terms of Turing completeness and of efficiency in solving hard problems, under different assumptions for information encoding, form and application of rules, and bounds on the main parameters defining the systems.
Topics & Concepts
Theory of computationComputer scienceNeural systemModels of neural computationComputationTuring machineTuringSpiking neural networkComplex systemEncoding (memory)Theoretical computer scienceArtificial neural networkExpressive powerCompleteness (order theory)Artificial intelligenceAlgorithmMathematicsNeuroscienceProgramming languageMathematical analysisBiologyDNA and Biological ComputingAdvanced biosensing and bioanalysis techniquesModular Robots and Swarm Intelligence