Zidong Wang - Selected Publications#

[1] L. Wang, Z. Wang, Q.-L. Han and G. Wei, Synchronization control for a class of discrete-time dynamical networks with packet dropouts: a coding-decoding-based approach, IEEE Transactions on Cybernetics, 48(8): 2437-2448, 2018.

This paper, which has been published in the No. 1 journal (out of 22) in computer science (cybernetics) according to ISI Web of knowledge, represents the first-ever attempt to develop coding-decoding-based approach for synchronizing discrete-time complex networks, investigate how the packet dropouts impact on the synchronization behaviours, and examine how such behaviours can be controlled. Latest convex analysis and stochastic analysis tools have been successfully applied and rigorous mathematical contributions have been made to the synchronization analysis issue. In particular, the way of proving the stochastically exponential synchronization in Theorems 1-2 has been quickly adopted in many later papers with 31 citations .

[2] H. Liu, Z. Wang, B. Shen and X. Liu, Event-triggered H-infinity state estimation for delayed stochastic memristive neural networks with missing measurements: the discrete time case, IEEE Transactions on Neural Networks and Learning Systems, 29(8): 3726-3737, 2018.

This is the first-ever paper that specifically deals with the event-triggered H-infinity state estimation for a new model of memristive neural networks exhibiting stochasticity and time-delays. A set of easy-to-test criteria/results for the estimation issues has been published in the best neural network journal, which has since been attracting extremely quick research attention from the community with 34 citations. In fact, the proposed model/methodologies have been immediately utilized by other researchers (as evidenced by the title of ‘highly cited paper’) who aim to further improve the initial results obtained and apply our developed algorithms to real-world applications.

[3] Y. Luo, Z. Wang and G. Wei, Fault detection for fuzzy systems with multiplicative noises under periodic communication protocols, IEEE Transactions on Fuzzy Systems, 26(4): 2384-2395, 2018.

This is the first paper published in the top journal on fuzzy systems that has opened up a new research branch in networked systems by making the first attempt to tackle the fuzzy fault detection problem with communication protocols. The new problem addressed and the new convex-analysis-based methodologies have quickly attracted research attention from the fuzzy control community leading to a number of journal citations. Part of the main results has later been referred in a monograph entitled “Performance Analysis and Synthesis for Discrete-Time Stochastic Systems with Network-Enhanced Complexities” published by CRC Press in 2018.

[4] L. Wang, Z. Wang, Q.-L. Han and G. Wei, Event-based variance-constrained H-infinity filtering for stochastic parameter systems over sensor networks with successive missing measurements, IEEE Transactions on Cybernetics, 48(3): 1007-1017, 2018.

As a highly cited paper (according to Web of Science) published in IEEE-TCYB (the top computer science journal in cybernetics), this paper has made a brave move to justify/introduce a new class of sensor networks with successive missing measurements. Two fundamental challenges have been elegantly handled, namely, how to deal with the asynchronous triggering of individual sensors and how to develop novel techniques to examine the impacts from the stochastic parameters. Such sensor networks have been quickly followed by other researchers (with 44 citations) to learn effective and efficient algorithms in saving renewable energy in resource-constrained environments.

[5] B. Shen, Z. Wang and H. Qiao, Event-triggered state estimation for discrete-time multidelayed neural networks with stochastic parameters and incomplete measurements, IEEE Transactions on Neural Networks and Learning Systems, 28(5): 1152-1163, 2017.

This paper has been published in the No. 2 journal (out of 103) in computer science (theory and methods) according to ISI Web of knowledge. A novel concept of event-triggered estimation is proposed to reflect the energy-saving need for monitoring recurrent neural networks (RNNS) and a novel methodology is developed by exploiting a time-varying real-valued function, the Kronecker product, as well as the recursive linear matrix inequalities. This ‘highly cited paper’ (85 citations) of IEEE-T-NNLS has opened up a brand new research venue for resource-constrained estimation of RNNS, and the proposed concept/methodology has been later adopted/exploited in many publications.

[6] D. Ding, Z. Wang, D. W. C. Ho and G. Wei, Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks, Automatica, 78: 231-240, 2017.

This is the first paper dealing with a radically new cyber-security problem for information transmissions over sensor networks. It is a substantial extension of the authors’ previous winning paper for the 2018 IET Premium Award entitled “Event-based security control for discrete-time stochastic systems”. This paper has solved two long-standing open problems: the first is how to effectively fusing unreliable data and the second is how to cope with complicated network couplings. Owing to its distinct merits and wide citations, this paper has been listed as both a highly cited paper and a hot paper soon after its publication with 140 citations.

[7] H Dong, Z Wang, DWC Ho, H Gao, Robust H-infinity fuzzy output-feedback control with multiple probabilistic delays and multiple missing measurements, IEEE Transactions on Fuzzy systems, 18(4): 712-725, 2010.

Published in the No. 1 journal (out of 114) in computer science (artificial intelligence) according to ISI Web of knowledge, this paper has opened up a new research branch in networked control systems by making the first attempt to tackle the fuzzy control problem with random packet losses and time-delays. The new problem addressed has quickly attracted research attention from the fuzzy control community leading to 171 journal citations. Part of the main results has later been referred in a monograph entitled “Filtering, Control and Fault Detection with Randomly Occurring Incomplete Information” published by Wiley in 2013.

[8] Y Liu, Z Wang, J Liang, X Liu, Synchronization and state estimation for discrete-time complex networks with distributed delays, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 38(5): 1314-1325, 2008.

This is the first paper dealing with the synchronization problem for an array of coupled complex discrete-time networks with the simultaneous presence of both the discrete and distributed time delays. This paper has solved two long-standing open problems: the first one is how to represent distributed time delays in the discrete-time domain and the second one is how to estimate the state for large-scale complex networks. Owing to its distinct merits, this paper has been accepted for publication WIHTOUT revision and has received the 3rd highest citations (among IEEE T-SMC-B papers published from 2008, 376 journal citations) .

[9] B Shen, Z Wang, X Liu, Bounded H-infinity synchronization and state estimation for discrete time-varying stochastic complex networks over a finite-horizon, IEEE Transactions on Neural Networks, 22(1): 145-157, 2011.

This paper has been published in the No. 1 journal (out of 50) in computer science (hardware and architecture) according to ISI Web of knowledge. A novel concept of bounded H-infinity synchronization is proposed to reflect the time-varying nature of the complex networks and a novel methodology is developed by exploiting a time-varying real-valued function, the Kronecker product, as well as the recursive linear matrix inequalities. The proposed concept/methodology have been later adopted/exploited in many publications, which is confirmed by 215 citations in refereed journals (the highest one among all IEEE T-NN papers published since 2011).

[10] J Liang, Z Wang, Y Liu, X Liu, Robust synchronization of an array of coupled stochastic discrete-time delayed neural networks, IEEE Transactions on Neural Networks, 19 (11): 1910-1921, 2008.

This is the first-ever paper that specifically deals with the synchronization problems for a new model of neural networks exhibiting stochasticity and time-delays. A set of easy-to-test criteria/results for the synchronizability issues has been published in the best neural network journal, which has since been attracting persistent research attention from the community in the past 5 years. In fact, the proposed model/methodologies have been frequently utilized by other researchers (as evidenced by the 153 journal citations) who aim to further improve the initial results obtained. Also, the algorithms developed have been successfully applied in cDNA microarray image segmentation problems.