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Papers in Collective Volumes
Yang, J., Chen R., Zhang G., Peng H., Wang J., & Riscos-Núñez A. (2018).  A Kernel-Based Membrane Clustering Algorithm. Enjoying Natural Computing: Essays Dedicated to Mario de Jesús Pérez-Jiménez on the Occasion of His 70th Birthday. 318-329.
Journal Papers
Peng, H., Wang J., & Pérez-Jiménez M. J. (2015).   Optimal multi-level thresholding with membrane computing. Digital Signal Processing. 37, 53–64.
Peng, H., Wang J., Shi P., Pérez-Jiménez M. J., & Riscos-Núñez A. (2015).  An automatic clustering algorithm inspired by membrane computing. Pattern Recognition Letters. 68(1), 34-40.
Wang, J., Hu J., Peng H., Pérez-Jiménez M. J., & Riscos-Núñez A. (2015).  Decision tree models induced by membrane systems. Romanian Journal of Information Science and Technology. 18(3), 228–239.
Peng, H., Bao T., Luo X., Wang J., Song X., Riscos-Núñez A., et al. (2020).  Dendrite P systems. Neural Networks. 127, 110 - 120. Abstract
Peng, H., Wang J., Pérez-Jiménez M. J., & Riscos-Núñez A. (2019).  Dynamic threshold neural P systems. Knowledge-Based Systems. 163, 875-884.
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
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
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.
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.
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
Peng, H., Wang J., Pérez-Jiménez M. J., & Riscos-Núñez A. (2014).  The framework of P systems applied to solve optimal watermarking problem. Signal Processing. 101, 256-265.
Peng, H., Wang J., Pérez-Jiménez M. J., Wang H., Shao J., & Wang T. (2013).  Fuzzy reasoning spiking neural P system for fault diagnosis. Information Sciences. 235, 106–116. Abstract
Wang, J., Peng H., Yu W., Ming J., Pérez-Jiménez M. J., Tao C., et al. (2019).  Interval-valued fuzzy spiking neural P systems for fault diagnosis of power transmission networks. Engineering Applications of Artificial Intelligence. 82, 102 - 109. Abstract
Li, B., Peng H., Luo X., Wang J., Song X., Pérez-Jiménez M. J., et al. (2021).  Medical Image Fusion Method Based on Coupled Neural P Systems in Nonsubsampled Shearlet Transform Domain. International Journal of Neural Systems. 31(1), 2050050.
Peng, H., Jiang Y., Wang J., & Pérez-Jiménez M. J. (2015).  Membrane clustering algorithm with hybrid evolutionary mechanisms. Journal of Software. 26(6), 1001-1012.
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.
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
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
Lv, Z., Bao T., Zhou N., Peng H., Huang X., Riscos-Núñez A., et al. (2021).  Spiking Neural P Systems with Extended Channel Rules. International Journal of Neural Systems. 31(1), 2050049.
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
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

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)