Home

Biblio

Export 837 results:
Sort by: Author [ Title (Desc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
F
Xian, R., Xiong X., Peng H., Wang J., Ramírez-de-Arellano-Marrero A., & Yang Q. (2024).  Feature fusion method based on spiking neural convolutional network for edge detection. Pattern Recognition. 147, 110112. Abstract
Wang, T., Zeng S., Zhang G., Pérez-Jiménez M. J., & Wang J. (2015).  Fault Section Estimation of Power Systems with Optimization Spiking Neural P Systems. Workshop on Membrane Computing 2015 (WMC2015), Satellite workshop of UCNC2015. 117-127.
Peng, H., Wang J., Ming J., Shi P., Pérez-Jiménez M. J., Yu W., et al. (2018).  Fault diagnosis of power systems using intuitionistic fuzzy spiking neural P systems. IEEE Transactions on Smart Grid.
Peng, H., Wang J., Shi P., Pérez-Jiménez M. J., & Riscos-Núñez A. (2017).  Fault diagnosis of power systems using fuzzy tissue-like P systems. Integrated Computer-Aided Engineering. vol. 24, no. 4, 401-411.
Wang, T., Zhang G., Zhao J., He Z., Wang J., & Pérez-Jiménez M. J. (2015).  Fault diagnosis of electric power systems based on fuzzy reasoning spiking neural P systems. IEEE Transactions on Power Systems. 30(3), 1182-1194. Abstract
Wang, T., Zhang G., & Pérez-Jiménez M. J. (2014).  Fault Diagnosis Models for Electric Locomotive Systems Based on Fuzzy Reasoning Spiking Neural P Systems. 15th Conference on Membrane Computing, pre-proceedings. 361-374.
Wang, J., Peng H., Tu M., Pérez-Jiménez M. J., & Shi P. (2016).  A Fault Diagnosis Method of Power Systems Based on an Improved Adaptive Fuzzy Spiking Neural P Systems and PSO Algorithms. Signal Processing. 25, 320-327. Abstract
Wang, T., Wang J., Fan Z., Wei X., Zang T., Pérez-Jiménez M. J., et al. (2017).  Fault diagnosis for multi-energy flows of energy internet: Framework and prospect. 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). 1-5.
Díaz-Pernil, D., Gutiérrez-Naranjo M. A., Pérez-Jiménez M. J., & Riscos-Núñez A. (2008).  A Fast Solution to the Partition Problem by Using Tissue-Like P Systems. (D. Kearney, V. Nguyen, G. Gioiosa, T. Hendtlass, Ed.).Third International Conference on Bio-Inspired Computing. 43 - 47.
Gutiérrez-Naranjo, M. A., Pérez-Jiménez M. J., & Riscos-Núñez A. (2005).  A fast P system for finding a balanced 2-partition. Soft Computing. 9(9), 673-678. Abstract
Cámpora Pérez, D. H., Neufeld N., & Riscos-Núñez A. (2019).  A Fast Local Algorithm for Track Reconstruction on Parallel Architectures. 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).
Orellana-Martín, D., Valencia-Cabrera L., & Pérez-Jiménez M. J. (2018).  The factorization problem: A new approach through membrane systems. Workshop on Membrane Computing, satellite workshop of 17th International Conference on Unconventional Computation and Natural Computation (UCNC 2018).
E
Martínez-del-Amor, M. A., Doncel-Ramírez A., Orellana-Martín D., & Pérez-Hurtado I. (2020).  Extracting Parallelism in Simulation Algorithms for PDP systems. 18th Brainstorming Week on Membrane Computing (BWMC2020). 79-90.
Macías-Ramos, L. F., Song T., Pan L., & Pérez-Jiménez M. J. (2014).  Extending SNP Systems Asynchronous Simulation Modes in P-Lingua. Twelfth Brainstorming Week on Membrane Computing (BWMC2014). 261-280.
Macías-Ramos, L. F., Pérez-Jiménez M. J., Song T., & Pan L. (2015).  Extending Simulation of Asynchronous Spiking Neural P Systems in P–Lingua. Fundamenta Informaticae. 136(3), 253-267.
Peng, H., Wang J., Shi P., Pérez-Jiménez M. J., & Riscos-Núñez A. (2016).  An extended membrane system with active membranes to solve automatic fuzzy clustering problems. International Journal of Neural Systems. 1-11. Abstract
Cordón-Franco, A., Gutiérrez-Naranjo M. A., Pérez-Jiménez M. J., & Riscos-Núñez A. (2005).  Exploring computation trees associated with P systems. Lecture Notes in Computer Science. 3365, 278-286. Abstract
Cao, H., Romero-Campero F. J., Heeb S., Cámara M., & Krasnogor N. (2010).  Evolving Cell Models for Systems and Synthetic Biology. Systems and Synthetic Biology. 4(1), 55-84. Abstract
García-Quismondo, M., Reed M. J., Chew F. S., Martínez-del-Amor M. A., & Pérez-Jiménez M. J. (2017).  Evolutionary response of a native butterfly to concurrent plant invasions: simulation of population dynamics. Ecological Modelling. 360, 410-424. Abstract
Zhang, G., Gheorghe M., Pan L., & Pérez-Jiménez M. J. (2014).  Evolutionary membrane computing: a comprehensive survey and new results. Information Sciences. 279, 528–551.
Cavaliere, M., Freund R., Leistch A., & Paun G. (2005).  Event-related outputs of computations in P systems. (Miguel A. Gutiérrez-Naranjo, Agustín Riscos-Núñez, Francisco J. Romero-Campero, Dragos Sburlan, Ed.).Third Brainstorming Week on Membrane Computing. 107-122.
Cavaliere, M., Freund R., Leistch A., & Paun G. (2006).  Event-related outputs of computations in P systems. Journal of Automata, Languages and Combinatorics. 11(3), 263-278. Abstract
Pérez-Jiménez, M. J. (1992).  Esquemas del Máximo en la Aritmética. 9+2 microfilms.
[Anonymous] (2018).  Enjoying Natural Computing: Essays Dedicated to Mario de Jesús Pérez-Jiménez on the Occasion of His 70th Birthday. (Carmen Graciani, Agustín Riscos-Núñez, Gheorghe Păun, Grzegorz Rozenberg, Arto Salomaa, Ed.). x+331.
Cecilia, J. M., Guerrero G. D., García J. M., Martínez-del-Amor M. A., Pérez-Jiménez M. J., & Ujaldón M. (2010).  Enhancing the Simulation of P Systems for the SAT Problem on GPUs. Symposium on Application Accelerators in High Performance Computing. Abstract