Mario J. Pérez-Jiménez

TL;DR: This work deals with several aspects concerning the formal verification of SN P systems and the computing power of some variants, and proposes a methodology based on the information given by the transition diagram associated with an SN P system which establishes the soundness and completeness of the system with respect to the problem it tries to resolve.

TL;DR: An extended spiking neural P system (ESNPS) has been proposed by introducing the probabilistic selection of evolution rules and multi-neurons output and a family of ESNPS, called optimization spiking Neural P system, are further designed through introducing a guider to adaptively adjust rule probabilities to approximately solve combinatorial optimization problems.

TL;DR: In this article, the authors present a selective bibliography of Membrane Computing applications, including bio-applications, computer science applications, linguistics applications, and language applications.

TL;DR: The results of case studies show that FDSNP is effective in diagnosing faults in power transmission networks for single and multiple fault situations with/without incomplete and uncertain SCADA data, and is superior to four methods reported in the literature in terms of the correctness of diagnosis results.

TL;DR: This work extends SN P systems by introducing some new ingredients (such as three types of neurons, fuzzy logic and new firing mechanism) and proposes the fuzzy reasoning spiking neural P systems (FRSN P systems), which are particularly suitable to model fuzzy production rules in a fuzzy diagnosis knowledge base and their reasoning process.