Opened Access Spiking Neural P systems with weights


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Autor: Wang, Jun
Hoogeboom, Hendrik Jan
Pan, Linqiang
Paun, Gheorghe
Pérez Jiménez, Mario de Jesús
Departamento: Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial
Fecha: 2010
Publicado en: Neural Computation, 22 (10), 2615-2646.
Tipo de documento: Artículo
Resumen: A variant of spiking neural P systems with positive or negative weights on synapses is introduced, where the rules of a neuron fire when the potential of that neuron equals a given value. The involved values—weights, firing thresholds, potential consumed by each rule—can be real (computable) numbers, rational numbers, integers, and natural numbers. The power of the obtained systems is investigated. For instance, it is proved that integers (very restricted: 1, −1 for weights, 1 and 2 for firing thresholds, and as parameters in the rules) suffice for computing all Turing computable sets of numbers in both the generative and the accepting modes. When only natural numbers are used, a characterization of the family of semilinear sets of numbers is obtained. It is shown that spiking neural P systems with weights can efficiently solve computationally hard problems in a nondeterministic way. Some open problems and suggestions for further research are formulated.
Cita: Wang, J., Hoogeboom, H.J., Pan, L., Paun, G. y Pérez Jiménez, M.d.J. (2010). Spiking Neural P systems with weights. Neural Computation, 22 (10), 2615-2646.
Tamaño: 586.8Kb
Formato: PDF


DOI: 10.1162/NECO_a_00022

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