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Ponencia
A Framework for Evolving Spiking Neural P Systems
(IMCS: International Membrane Computing Society, 2019)
In current literature, there is a lack of research on the optimization of spiking neural P systems (SN P systems) and, consequently, also a lack of automation to do this process of optimization. We address this gap by ...
Ponencia
CuSNP: Spiking Neural P Systems Simulators in CUDA
(IMCS: International Membrane Computing Society, 2016)
Spiking neural P systems (in short, SN P systems) are models of computation inspired by biological neurons. In this work, we report our ongoing e orts to improve simulators for SN P systems. CuSNP is a project involving ...
Ponencia
Temporal Fuzzy Reasoning Spiking Neural P Systems with Real Numbers for Power System Fault Diagnosis
(IMCS: International Membrane Computing Society, 2015)
This paper proposes a temporal fuzzy reasoning spiking neural P sys- tem with real numbers (rTFRSN P system) and its corresponding fault diagnosis method called FDTSNP to diagnose faults in a power system. The introduction of ...
Ponencia
Improving Simulations of Spiking Neural P Systems in NVIDIA CUDA GPUs: CuSNP
(Fénix, 2016)
Spiking neural P systems (in short, SN P systems) are parallel models of computations inspired by the spiking ( ring) of biological neurons. In SN P systems, neurons function as spike processors and are placed on nodes ...
Ponencia
Nondeterminism in Spiking Neural P Systems: Algorithms and Simulations
(Xihua University, 2017)
Spiking Neural P system (or SN P system) is a computing model based on the neurons in a living being. It is composed of neurons containing spikes interconnected by synapses. Each neuron contain a set of rules which will ...
Ponencia
A Framework for Evolving Spiking Neural P Systems with Rules on Synapses
(IMCS: International Membrane Computing Society, 2019)
In this paper, we present a genetic algorithm framework for evolving Spiking Neural P Systems with rules on synapses (RSSNP systems, for short). Starting with an initial RSSNP system, we use the genetic algorithm framework ...