The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Extended Dissipative State Estimation for Markov Jump Neural Networks With Unreliable Links
Abstract
This paper is concerned with the problem of extended dissipativity-based state estimation for discrete-time Markov jump neural networks (NNs), where the variation of the piecewise time-varying transition probabilities of Markov chain is subject to a set of switching signals satisfying an average dwell-time property. The communication links between the NNs and the estimator are assumed to be imperfect, where the phenomena of signal quantization and data packet dropouts occur simultaneously. The aim of this paper is to contribute with a Markov switching estimator design method, which ensures that the resulting error system is extended stochastically dissipative, in the simultaneous presences of packet dropouts and signal quantization stemmed from unreliable communication links. Sufficient conditions for the solvability of such a problem are established. Based on the derived conditions, an explicit expression of the desired Markov switching estimator is presented. Finally, two illustrated examples are given to show the effectiveness of the proposed design method.
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Self-citationGlobal asymptotic and robust stability of recurrent neural networks with time delays
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Exponential Synchronization of Linearly Coupled Neural Networks With Impulsive Disturbances
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Loyola-Gonzalez, O. (2019) · IEEE Access · doi:10.1109/access.2019.2949286 · Cited by 559
Finite-Time Event-Triggered $\mathcal{H}_{\infty }$ Control for T–S Fuzzy Markov Jump Systems
Shen, H., Li, F., Yan, H., Karimi, H. R., & Lam, H.-K. (2018) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2017.2788891 · Cited by 458
Self-citation
Metadata
- Authors
- Shen, H., Zhu, Y., Zhang, L., & Park, J. H.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2017-02
- Volume
- 28
- Issue
- 2
- Pages
- 346-358
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W2342488082
- Cited by
- 489
- References
- 22
- FWCI
- 85.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- Shen, H., Zhu, Y., Zhang, L., & Park, J. H. (2017). Extended Dissipative State Estimation for Markov Jump Neural Networks With Unreliable Links. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2015.2511196
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