Home

Biblio

Export 64 results:
Sort by: Author Title [ Type (Desc)] Year
Filters: First Letter Of Last Name is W  [Clear All Filters]
Journal Papers
Wang, T., Wei X., Huang T., Wang J., Peng H., Pérez-Jiménez M. J., et al. (2019).  Modeling Fault Propagation Paths in Power Systems: A New Framework Based on Event SNP Systems With Neurotransmitter Concentration. IEEE Access. 7, 12798-12808.
Peng, H., Shi P., Wang J., Riscos-Núñez A., & Pérez-Jiménez M. J. (2017).  Multiobjective fuzzy clustering approach based on tissue-like membrane systems. Knowledge-Based Systems. 125, 74-82.
Peng, H., Lv Z., Li B., Luo X., Wang J., Song X., et al. (2020).  Nonlinear Spiking Neural P Systems. International Journal of Neural Systems. 30(10), 2050008.
Ibarra, O., Paun A., Paun G., Rodríguez-Patón A., Sosik P., & Woodworth S. (2007).  Normal forms for spiking neural P systems. Theoretical Computer Science. 372(2-3), 196-217. Abstract
Peng, H., Wang J., Pérez-Jiménez M. J., & Shi P. (2013).  A novel image thresholding method based on membrane computing and fuzzy entropy. Journal of Intelligent and Fuzzy Systems. 2, 229-237. Abstract
Yuan, W., Zhang G., Pérez-Jiménez M. J., Wang T., & Huang Z. (2016).  P systems based computing polynomials: design and formal verification. Natural Computing. 15(4), 591–596.
Bai, X., Huang Y., Peng H., Wang J., Yang Q., Orellana-Martín D., et al. (2023).  Sequence recommendation using multi-level self-attention network with gated spiking neural P systems. Information Sciences. 119916. Abstract
Valencia-Cabrera, L., Wu T., Zhang Z., Pan L., & Pérez-Jiménez M. J. (2017).  A simulation software tool for cell-like spiking neural P systems. Romanian Journal of Information Science and Technology. vol. 20, no. 1, 71-84.
Peng, H., Li B., Wang J., Song X., Wang T., Valencia-Cabrera L., et al. (2019).  Spiking neural P systems with inhibitory rules. Knowledge-Based Systems. 105064. Abstract
Peng, H., Li B., Wang J., Song X., Wang T., Valencia-Cabrera L., et al. (2020).  Spiking neural P systems with inhibitory rules. Knowledge-Based Systems. 188, 105064. Abstract
Wang, J., Hoogeboom H. J., Pan L., Paun G., & Pérez-Jiménez M. J. (2010).  Spiking Neural P Systems with Weights. Neural Computation. 22(10), 2615-2646. Abstract
Peng, H., Wang J., Pérez-Jiménez M. J., & Riscos-Núñez A. (2015).  An unsupervised learning algorithm for membrane computing. Information Sciences. 304, 80–91.
Wang, T., Wei X., Wang J., Huang T., Peng H., Song X., et al. (2020).  A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies. Engineering Applications of Artificial Intelligence. 92, 103680. Abstract
Wang, T., Zhang G., Pérez-Jiménez M. J., & Cheng J. (2015).  Weighted Fuzzy Reasoning Spiking Neural P Systems: Application to Fault Diagnosis in Traction Power Supply Systems of High-Speed Railways. Journal of Computational and Theoretical Nanoscience. 12(7), 1003-1114. Abstract
Wang, J., Shi P., Peng H., Pérez-Jiménez M. J., & Wang T. (2013).  Weighted Fuzzy Spiking Neural P Systems. IEEE Transactions on Fuzzy Systems. 2, 209-220. Abstract
Contributions to Book Chapters
Pérez-Jiménez, M. J., Riscos-Núñez A., Romero-Jiménez Á., & Woods D. (2010).  Complexity: membrane division, membrane creation. (Gheorghe Paun, Grzegorz Rozenberg, Arto Salomaa, Ed.).The Oxford Handbook of Membrane Computing. 302-336.
Pérez-Jiménez, M. J., & Yokomori T. (2009).  Membrane Computing schema: A new approach to computation using string insertion. (A. Condon, D. Harel, J. N. Kon, Arto Salomaa, Eric Winfree, Ed.).Algorithmic Bioprocesses. V, 293-309. Abstract
Paun, G., & Pérez-Jiménez M. J. (2009).  Spiking neural P systems: Recent results, research topics. (A. Condon, D. Harel, J. N. Kon, Arto Salomaa, Eric Winfree, Ed.).Algorithmic Bioprocesses. V, 273-291. Abstract
Conference Contributions
Murphy, N., & Woods D. (2007).  Active membrane systems without charges and using only symmetric elementary division characterise P. (George Eleftherakis, Petros Kefalas, Gheorghe Paun, Grzegorz Rozenberg, Arto Salomaa, Ed.).8th Workshop on Membrane Computing. 4860, 367-384.
Wang, T., Zhang G., & Pérez-Jiménez M. J. (2014).  Application of Weighted Fuzzy Reasoning Spiking Neural P Systems to Fault Diagnosis in Traction Power Supply Systems of High-speed Railways. Twelfth Brainstorming Week on Membrane Computing (BWMC2014). 329-350.
Valencia-Cabrera, L., Pérez-Jiménez M. J., Chen X., Wang B., & Zeng X. X. (2015).  Basic virus machines. 16th International Conference on Membrane Computing (CMC16). 323-342.
Murphy, N., & Woods D. (2008).  A characterisation of NL using membrane systems without charges and dissolution. (Cristian Calude, José F. Costa, Rudolf Freund, Marion Oswald, Grzegorz Rozenberg, Ed.).Unconventional Computation, UC'08. 5204, 164-176.
Murphy, N., & Woods D. (2009).  The computational complexity of uniformity and semi-uniformity in membrane systems. 7th Brainstorming Week on Membrane Computing. II, 73-84. Abstract
Peng, H., Wang J., Pérez-Jiménez M. J., Riscos-Núñez A., Xiao J., & Zhang G. (2015).  Decision Tree Models Induced by Membrane Systems. Workshop on Membrane Computing 2015 (WMC2015), Satellite workshop of UCNC2015. 107-116.
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.

Statistics

  • Books (11)
  • Edited Books (28)
  • Contributions to Book Chapters (42)
  • Journal Papers (421)
  • Papers in Collective Volumes (0)
  • Technical Reports (3)
  • Conference Contributions (289)
  • Conference Proceedings (38)