Mario J. Pérez-Jiménez

dblp:p/MarioJPerezJimenez · also Mario de J. Pérez-Jiménez, Mario de Jesús Pérez-Jiménez · DBLP profile ↗
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6ranked-venue papers in the field
0as first author
2since 2021 · last 2026
0000-0002-5055-0102ORCID · verified

Domains — venue-derived; a paper can count in several

Knowledge Engineering, Semantic Web & Information Systems · 5Other / Interdisciplinary · 1
YearPublicationVenuePosition
2026 A novel fault section identification method for smart substations considering information tampering based on multi-pulse spiking neural P systems
Tao Wang 0029, Wei Liu 0142, Peng Wang 0017, Mario J. Pérez-Jiménez
Inf. Sci.5
2024 Sequence recommendation using multi-level self-attention network with gated spiking neural P systems
Xinzhu Bai, Yanping Huang, Hong Peng 0001, Jun Wang 0013, Qian Yang 0002, David Orellana-Martín, Antonio Ramírez-de-Arellano, Mario J. Pérez-Jiménez
Inf. Sci.8
2015 An unsupervised learning algorithm for membrane computing
Hong Peng 0001, Jun Wang 0013, Mario J. Pérez-Jiménez, Agustin Riscos-Núñez
Inf. Sci.3
2014 Evolutionary membrane computing: A comprehensive survey and new results
Gexiang Zhang, Marian Gheorghe 0001, Linqiang Pan, Mario J. Pérez-Jiménez
Inf. Sci.4
2013 Fuzzy reasoning spiking neural P system for fault diagnosis
Hong Peng 0001, Jun Wang 0013, Mario J. Pérez-Jiménez, Tao Wang 0029
Inf. Sci.3
2009 On the efficiency of cell-like and tissue-like recognizing membrane systems
abstract
Cell-like recognizing membrane systems are computational devices in the framework of membrane computing inspired from the structure of living cells, where biological membranes are arranged hierarchically. In this paper tissue-like recognizing membrane systems are presented. The idea is to consider that membranes are placed in the nodes of a graph, mimicking the cell intercommunication in tissues. In this context, polynomial complexity classes associated with recognizing membrane systems can be defined. We recall the definition for cell-like systems, and we introduce the corresponding complexity classes for the tissue-like case. Moreover, in this paper two efficient solutions to the satisfiability problem are analyzed and compared from a complexity point of view. © 2009 Wiley Periodicals, Inc.
Miguel Angel Gutiérrez-Naranjo, Mario J. Pérez-Jiménez, Agustin Riscos-Núñez, Francisco José Romero-Campero
Int. J. Intell. Syst.2