Recursive Filtering for Stochastic Complex Networks via Hybrid Transmission Protocol

Abstract In this paper, the problem of the recursive filtering is addressed for the stochastic nonlinear complex networks under the hybrid transmission protocol and amplify‐and‐forward relays. The novel hybrid transmission protocol is proposed that integrates the weighted try‐once‐discard protocol with the event‐triggered protocol. A key feature of the protocol is the ability to dynamically and flexibly adjust the number of transmitted packets by utilizing dual thresholds. Furthermore, the protocol considers factors such as dual thresholds and priority levels, which contribute to optimizing the balance between algorithm performance and network load. At the same time, the predictive compensation strategy is proposed to mitigate the degradation of estimation accuracy. Given that measurement is affected by random sensor gain degradation, the amplify‐and‐forward relays are employed to improve communication quality and facilitate long‐range transmission. The main objective of this paper is to establish a novel recursive filtering algorithm for stochastic nonlinear complex networks. To address the multiple effects of uncertain inner coupling, random sensor gain degradation, amplify‐and‐forward relays and the hybrid transmission protocol, the upper bound on the filtering error covariance is guaranteed and minimized by selecting the desired filter gain. Subsequently, a sufficient condition with a rigorous theoretical proof is provided to ensure that the filtering error covariance is uniformly bounded. Ultimately, a practical simulation is employed to demonstrate the reliable performance and advantages of the designed filtering algorithm.