A Dynamic Event-Triggered Approach to Recursive Filtering for Complex Networks With Switching Topologies Subject to Random Sensor Failures

This article deals with the recursive filtering issue for a class of nonlinear complex networks (CNs) with switching topologies, random sensor failures and dynamic event-triggered mechanisms. A Markov chain is utilized to characterize the switching behavior of the network topology. The phenomenon of...

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Bibliographic Details
Published in:	IEEE transaction on neural networks and learning systems Vol. 31; no. 10; pp. 4381 - 4388
Main Authors:	Li, Qi, Wang, Zidong, Li, Nan, Sheng, Weiguo
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.10.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Complex networks Complex networks (CNs) Covariance dynamic event-triggered mechanisms (ETMs) Dynamic scheduling Failure Filters Heuristic algorithms IIR filters Markov chains Markov processes Network topologies recursive filtering Recursive methods sensor failures Sensors Stochasticity Switches Switching switching topologies Topology Upper bounds
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
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