Recursive Filtering for Discrete-Time Stochastic Complex Networks Under Bit-Rate Constraints: A Locally Minimum Variance Approach

Wang, Licheng; Wang, Zidong; Zhao, Di; Liu, Yang; Wei, Guoliang

doi:10.1109/tac.2023.3349102

IEEE Trans. Automat. Contr.

2024

DOI: 10.1109/tac.2023.3349102

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Recursive Filtering for Discrete-Time Stochastic Complex Networks Under Bit-Rate Constraints: A Locally Minimum Variance Approach

Licheng Wang,

Zidong Wang,

Di Zhao

et al.

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Cited by 7 publications

References 38 publications

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Recursive multi‐sensor fusion estimation under the coding‐based relay network

Zhang,

Liu,

Deng

2024

Asian Journal of Control

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This paper studies the recursive fusion estimation issue for a class of linear time‐varying multi‐sensor systems with amplify‐and‐forward (AF) relays. The AF relay is located between the sensor and the estimator to forward measurement signals for facilitating long‐distance transmission. A binary encoding scheme is used to regulate signal transmission via a digital network where the signal is encoded into a bit string and decoded at the endpoint of the receiver. Because of the uncertainty of the network and the existence of channel noises, a set of Bernoulli distributed random variables is introduced to characterize the random bit flip phenomenon. The purpose of the addressed problem is to design a fusion estimator to simultaneously reflect the impact of multiplicative noises, the AF relay, the binary encoding scheme, and the random bit flip on the filtering error covariance. First of all, an upper bound for the filtering error covariance of the local estimator can be acquired, and by minimizing such an upper bound, the parametric form of the gain matrix is obtained. Subsequently, the fusion estimation is given based on the covariance intersection fusion strategy. Finally, a simulation example is presented to verify the effectiveness of the proposed multi‐sensor fusion estimation.

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Recursive multi‐sensor fusion estimation under the coding‐based relay network

Zhang,

Liu,

Deng

2024

Asian Journal of Control

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Hidden Markov model‐based filtering for 2‐D Markov jump Roesser systems subject to analog fading channels

Ni,

Li,

et al. 2024

Asian Journal of Control

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This article considers the filtering problem for 2‐D Markov jump Roesser systems, in which the measurement signal is transmitted via analog fading channels. The time‐varying amplitude attenuation of the analog fading channels is described by the fading gain modeled as a random variable. The hidden Markov model is used to deal with the mode mismatch phenomenon between the plant and the filter, then a full‐order asynchronous filter is designed for 2‐D Markov jump Roesser systems under analog fading channels. The purpose is to introduce a filter to guarantee that the filtering error system is not only asymptotically mean square stable, but also satisfies the disturbance attenuation performance. An improved decoupling method is proposed to acquire the 2‐D filter parameters such that the conservatism of the 2‐D filter designed law can be effectively reduced. Finally, a verification example and Darboux equation are given to illustrate the validity of the introduced asynchronous filter design law.

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Secure consensus for multiagent systems with hybrid cyber attacks: A multi-round-robin protocol-based approach

Liu,

Zheng,

Zha

et al. 2024

Information Sciences

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Recursive Filtering for Discrete-Time Stochastic Complex Networks Under Bit-Rate Constraints: A Locally Minimum Variance Approach

Cited by 7 publications

References 38 publications

Recursive multi‐sensor fusion estimation under the coding‐based relay network

Recursive multi‐sensor fusion estimation under the coding‐based relay network

Hidden Markov model‐based filtering for 2‐D Markov jump Roesser systems subject to analog fading channels

Secure consensus for multiagent systems with hybrid cyber attacks: A multi-round-robin protocol-based approach

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