Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume 31, Issue 3, Pages 762-771Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2019.2909747
Keywords
Discrete-time genetic regulatory networks (GRN); distributed dissipative state estimation; Markov jump parameters; round-robin scheduling (RRS)
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Funding
- National Natural Science Foundation of China [61873002, 61703004, 61503002, 61673178]
- National Natural Science Foundation of Anhui Province [1708085MF165, 1808085QA18]
- University Excellent Young Talents Foundation of Anhui Province [gxyqZD2017041]
- China Postdoctoral Science Foundation [2018M632206]
- Basic Science Research Programs through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2017R1A2B2004671]
- National Research Foundation of Korea [22A20130000136] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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The distributed dissipative state estimation issue of Markov jump genetic regulatory networks subject to round-robin scheduling is investigated in this paper. The system parameters randomly change in the light of a Markov chain. Each node in sensor networks communicates with its neighboring nodes in view of the prescribed network topology graph. The round-robin scheduling is employed to arrange the transmission order to lessen the likelihood of the occurrence of data collisions. The main goal of the work is to design a compatible distributed estimator to assure that the distributed error system is strictly gamma-stochastically dissipative. By applying the Lyapunov stability theory and a modified matrix decoupling way, sufficient conditions are derived by solving some convex optimization problems. An illustrative example is given to verify the validity of the provided method.
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