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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., 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., Hoogeboom H. J., Pan L., & Paun G. (2009).  Spiking neural P systems with weights and thresholds. (Gheorghe Paun, Mario J. Pérez-Jiménez, Agustín Riscos-Núñez, Ed.).10th Workshop on Membrane Computing. 514-533. 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.
Wang, T., Zhang G., & Pérez-Jiménez M. J. (2015).  Fuzzy Membrane Computing: Theory and Applications. International Journal of Computers, Communications and Control. 10(6), 904-935. Abstract
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.
Wang, T., Wei X., Huang T., Wang J., Valencia-Cabrera L., Fan Z., et al. (2019).  Cascading Failures Analysis Considering Extreme Virus Propagation of Cyber-Physical Systems in Smart Grids. Complexity. 2019, 1-15.
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.
Woods, D., Murphy N., Pérez-Jiménez M. J., & Riscos-Núñez A. (2009).  Membrane dissolution and division in P. Lecture Notes in Computer Science. 5717, 262-276. Abstract
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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
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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.
Ye, L., Zheng J., Guo P., & Pérez-Jiménez M. J. (2019).  Solving the 0-1 Knapsack Problem by Using Tissue P System With Cell Division. IEEE Access. 7, 66055-66067.
Yuan, W., Zhang G., Pérez-Jiménez M. J., Wang T., & Huan Z. (2015).  P systems based computing polynomials: Design and formal verification. Asian Conference on Membrane Computing (ACMC 2015). 1, 1-9. 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.
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Zandron, C., Leporati A., Ferretti C., Mauri G., & Pérez-Jiménez M. J. (2008).  On the computational efficiency of polarizationless recognizer P systems with strong division and dissolution. 6th Brainstorming Week on Membrane Computing. 6, 261-274. Abstract
Zandron, C., Leporati A., Ferretti C., Mauri G., & Pérez-Jiménez M. J. (2008).  On the computational efficiency of polarizationless recognizer P systems with strong division and dissolution. Fundamenta Informaticae. 87(1), 79-91. Abstract
Zang, T., Lei J., Wei X., Huang T., Wang T., Pérez-Jiménez M. J., et al. (2019).  Adjacent Graph Based Vulnerability Assessment for Electrical Networks Considering Fault Adjacent Relationships Among Branches. IEEE Access. 7, 88927-88936. Abstract
Zeng, X. X., Pan L., & Pérez-Jiménez M. J. (2014).  Small universal simple Spiking Neural P Systems with weights. Science China. Information Sciences. 57(9), 1-11. Abstract
Zeng, X. X., Adorna H., Martínez-del-Amor M. A., & Pan L. (2010).  When Matrices Meet Brains. Eighth Brainstorming Week on Membrane Computing. 255-266.
Zeng, X. X., Adorna H., Martínez-del-Amor M. A., Pan L., & Pérez-Jiménez M. J. (2010).  Matrix representation of Spiking Neural P Systems. (Marian Gheorghe, Thomas Hinze, Gheorghe Paun, Ed.).Eleventh International Conference on Membrane Computing (CMC11). 425-439. Abstract
Zeng, X. X., Adorna H., Martínez-del-Amor M. A., Pan L., & Pérez-Jiménez M. J. (2011).  Matrix representation of Spiking Neural P systems. Lecture Notes in Computer Science. 6501, 377-392. Abstract
Zhang, G., Zhu M., Yang Q., Rong H., Yuan W., & Pérez-Jiménez M. J. (2017).  P systems based computing polynomials with integer coefficients: Design and formal verification. Asian Conference on Membrane Computing (ACMC 2017). 416-443.
Zhang, X., Niu Y., Pan L., & Pérez-Jiménez M. J. (2011).  Linear Time Solution to Prime Factorization by Tissue P Systems with Cell Division. International Journal of Natural Computing Research. 2(3), 49-60. 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.