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Asynchronous \(H_\infty \) Filtering for Singular Markov Jump Neural Networks with Mode-Dependent Time-Varying Delays

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Abstract

This article proposes asynchronous \(H_\infty \) filtering for singular Markov jump neural networks with mode-dependent time-varying delays. Firstly, regularity and impulse-freeness are acquired by singular value decomposition technique, stochastic stability conditions and \(H_\infty \) performance index are obtained by Lyapunov–Krasovskill functional method. Then, a hidden Markov model is used to describe asynchronism between the original system and filter, and asynchronous filtering is realized by virtue of linear matrix inequalities. In the end, the practicability of proposed method is verified by a numerical example and an analog resistance-capacitance network circuit system.

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Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

References

  1. Wang Z, Wang Y, Liu Y (2010) Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time delays. IEEE Trans Neural Netw 21(1):11–25

    Article  Google Scholar 

  2. Wu E, Yang X, Xu C, Alsaadi FE, Hayat T (2018) Finite-time synchronization of complex-valued delayed neural networks with discontinuous activations. Asian J Control 21(1):1–11

    MathSciNet  MATH  Google Scholar 

  3. Wang Z, Yang F, Ho DWC, Liu X (2007) Robust \(H_{\infty }\) control for networked systems with random packet losses. IEEE Trans Syst Man Cybern Part B Cybern 37(4):916–924

    Google Scholar 

  4. Tang R, Yang X, Wan X (2019) Finite-time cluster synchronization for a class of fuzzy cellular neural networks via non-chattering quantized controllers. Neural Netw 113:79–90

    Article  MATH  Google Scholar 

  5. Liu W, Wang Z, Liu X, Zeng N, Liu Y, Alsaadi FE (2017) A survey of deep neural network architectures and their applications. Neurocomputing 234:11–26

    Article  Google Scholar 

  6. Huo S, Chen M, Shen H (2017) Non-fragile mixed \(H_\infty \) and passive asynchronous state estimation for Markov jump neural networks with randomly occurring uncertainties and sensor nonlinearity. Neurocomputing 227:46–53

    Article  Google Scholar 

  7. Yang X, Liu Y, Cao J, Rutkowski L (2020) Synchronization of coupled time-delay neural networks with mode-dependent average dwell time switching. IEEE Trans Neural Netw Learn Syst 31(12):5483–5496

    Article  MathSciNet  Google Scholar 

  8. Li Q, Zhu Q, Zhong S, Zhong F (2017) Extended dissipative state estimation for uncertain discrete-time Markov jump neural networks with mixed time delays. ISA Trans 66:200–208

    Article  Google Scholar 

  9. Li H, Wu Y, Chen M, Lu R (2021) Adaptive multigradient recursive reinforcement learning event-triggered tracking control for multiagent systems. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2021.3090570

    Article  Google Scholar 

  10. Zou Y, Su H, Tang R, Yang X (2021) Finite-time bipartite synchronization of switched competitive neural networks with time delay via quantized control. ISA Trans. https://doi.org/10.1016/j.isatra.2021.06.015

    Article  Google Scholar 

  11. Tian Y, Wang Z (2020) Stability analysis and generalised memory controller design for delayed T–S fuzzy systems via flexible polynomial-based functions. IEEE Trans Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.3046338

    Article  Google Scholar 

  12. Li F, Shen H, Chen M, Kong Q (2015) Non-fragile finite-time \(l_2\) - \(l _\infty \) state estimation for discrete-time Markov jump neural networks with unreliable communication links. Appl Math Comput 271:467–481

    MathSciNet  MATH  Google Scholar 

  13. Xia W, Li Y, Chu Y, Xu S, Chen W, Zhang Z (2019) Observer-based mixed passive and \(H_\infty \) control for uncertain Markovian jump systems with time delays using quantized measurements. Nonlinear Anal Hybrid Syst 31:233–246

    Article  MathSciNet  MATH  Google Scholar 

  14. Chen W, Chen J, Zheng W (2020) Delay-dependent stability and hybrid \(L_2\times l_2\)-gain analysis of linear impulsive time-delay systems: a continuous timer-dependent Lyapunov-like functional approach. Automatica 120:109119

    Article  MATH  Google Scholar 

  15. Ma Y, Zheng Y (2018) Delay-dependent stochastic stability for discrete singular neural networks with Markovian jump and mixed time-delays. Neural Comput Appl 29:111–122

    Article  Google Scholar 

  16. Xu S, Zheng W, Zou Y (2009) Passivity analysis of neural networks with time-varying delays. IEEE Trans Circuits Syst II Express Briefs 56(4):325–329

    Google Scholar 

  17. Dai M, Xia J, Xia H, Shen H (2019) Event-triggered passive synchronization for Markov jump neural networks subject to randomly occurring gain variations. Neurocomputing 331:403–411

    Article  Google Scholar 

  18. Ali MS, Gunasekaran N, Rani ME (2017) Robust stability of Hopfield delayed neural networks via an augmented L–K functional. Neurocomputing 234:198–204

    Article  Google Scholar 

  19. Shen Y, Wu Z, Shi P, Su H, Huang T (2019) Asynchronous filtering for Markov jump neural networks with quantized outputs. IEEE Trans Syst Man Cybern Syst 49(2):433–443

    Article  Google Scholar 

  20. Tian Y, Wang Z (2020) Finite-time extended dissipative filtering for singular T–S fuzzy systems with nonhomogeneous Markov Jumps. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2020.3030503

    Article  Google Scholar 

  21. Zhuang G, Xia J, Feng J, Sun W, Zhang B (2021) Admissibilization for implicit jump systems with mixed retarded delays based on reciprocally convex integral inequality and Barbalat’s lemma. IEEE Trans Syst Man Cybern Syst 51(11):6808–6818

  22. Xu S, Lam J, Zou Y, Li J (2009) Robust admissibility of time-varying singular systems with commensurate time delays. Automatica 45(11):2714–2717

    Article  MathSciNet  MATH  Google Scholar 

  23. Zhang B, Xu S, Ma Q, Zhang Z (2019) Output-feedback stabilization of singular LPV systems subject to inexact scheduling parameters. Automatica 104:1–7

    Article  MathSciNet  MATH  Google Scholar 

  24. Feng Z, Shi P (2017) Sliding mode control of singular stochastic Markov jump systems. IEEE Trans Autom Control 62(8):4266–4273

    Article  MathSciNet  MATH  Google Scholar 

  25. Jiang B, Kao Y, Karimi HR, Gao C (2018) Stability and stabilization for singular switching semi-Markovian jump systems with generally uncertain transition rates. IEEE Trans Autom Control 63(11):3919–3926

    Article  MathSciNet  MATH  Google Scholar 

  26. Qi W, Zong G, Zheng W (2021) Adaptive event-triggered SMC for stochastic switching systems with semi-Markov process and application to boost converter circuit model. IEEE Trans Circuits Syst Regul Pap 68(2):786–796

    Article  MathSciNet  Google Scholar 

  27. Tang R, Su H, Zou Y, Yang X (2021) Finite-time synchronization of Markovian coupled neural networks with delays via intermittent quantized control: linear programming approach. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2021.3069926

    Article  Google Scholar 

  28. Zhuang G, Su S, Xia J, Sun W (2021) HMM-based asynchronous \(H_\infty \) filtering for fuzzy singular Markovian switching systems with retarded time-varying delays. IEEE Trans Cybern 51(3):1189–1203

    Article  Google Scholar 

  29. Tian Y, Wang Z (2021) Dissipative filtering for singular Markovian jump systems with generally hybrid transition rates. Appl Math Comput 411:126492

  30. Yang G, Kao B, Park JH, Kao Y (2019) \(H_\infty \) performance for delayed singular nonlinear Markovian jump systems with unknown transition rates via adaptive control method. Nonlinear Anal Hybrid Syst 33:33–51

    Article  MathSciNet  MATH  Google Scholar 

  31. Zhou S, Ren W, Lam J (2011) Stabilization for T–S model based uncertain stochastic systems. Inf Sci 181(4):779–791

    Article  MathSciNet  MATH  Google Scholar 

  32. Zhuang G, Xia J, Ma Q, Sun W, Wang Y (2021) Event-triggered \(H_\infty \) feedback control for delayed singular jump systems based on sampled observer and exponential detector. Int J Robust Nonlinear Control 31(15):7298–7316

    Article  MathSciNet  Google Scholar 

  33. Zhao Z, Wang Z, Zou L, Liu H (2018) Finite-horizon \(H_\infty \) state estimation for artificial neural networks with component-based distributed delays and stochastic protocol. Neurocomputing 321:169–177

    Article  Google Scholar 

  34. Liu G, Park JH, Xu S, Zhuang G (2019) Robust non-fragile \(H_\infty \) fault detection filter design for delayed singular Markovian jump systems with linear fractional parametric uncertainties. Nonlinear Anal Hybrid Syst 32:65–78

    Article  MathSciNet  MATH  Google Scholar 

  35. Chen W, Gao F, Liu G, Xu S, Zhang Z (2021) New reliable \(H_\infty \) filter design for singular Markovian jump time-delay systems with sensor failures. Int J Robust Nonlinear Control 31(9):4361–4377

    Article  MathSciNet  Google Scholar 

  36. Liu X, Ho DWC, Song Q, Xu W (2019) Finite/fixed-time pinning synchronization of complex networks with stochastic disturbances. IEEE Trans Cybern 49(6):2398–2403

    Article  Google Scholar 

  37. Tao J, Lu R, Su H, Shi P, Wu Z (2018) Asynchronous filtering of nonlinear Markov jump systems with randomly occurred quantization via T–S fuzzy models. IEEE Trans Fuzzy Syst 26(4):1866–1877

    Google Scholar 

  38. Shi P, Zhang Y, Chadli M, Agarwal RK (2016) Mixed H-infinity and passive filtering for discrete fuzzy neural networks with stochastic jumps and time delays. IEEE Trans Neural Netw Learn Syst 27(4):903–909

    Article  MathSciNet  Google Scholar 

  39. Liu J, Xia J, Tian E, Fei S (2018) Hybrid-driven-based \(H_\infty \) filter design for neural networks subject to deception attacks. Appl Math Comput 320:158–174

    MathSciNet  MATH  Google Scholar 

  40. Yang X, Wan X, Cheng Z, Cao J, Liu Y, Rutkowski L (2021) Synchronization of switched discrete-time neural networks via quantized output control with actuator fault. IEEE Trans Neural Netw Learn Syst 32(9):4191–4201

    Article  MathSciNet  Google Scholar 

  41. Zhang W, Yang X, Yang S, Alsaedi A (2021) Finite-time and fixed-time bipartite synchronization of complex networks with signed graphs. Math Comput Simul 188:319–329

    Article  MathSciNet  MATH  Google Scholar 

  42. Zhang W, Yang X, Yang S, Huang C, Alssaadi FE (2021) Fixed-time control of competitive complex networks. Neural Comput Appl 33:7943–7951

    Article  Google Scholar 

  43. Zhou Y, Wan X, Huang C, Yang X (2020) Finite-time stochastic synchronization of dynamic networks with nonlinear coupling strength via quantized intermittent control. Appl Math Comput 376:125157

    MathSciNet  MATH  Google Scholar 

  44. Liu X, Ho DWC, Xie C (2020) Prespecified-time cluster synchronization of complex networks via a smooth control approach. IEEE Trans Cybern 50(4):1771–1775

    Article  Google Scholar 

  45. Zhuang G, Sun W, Su S, Xia J (2021) Asynchronous feedback control for delayed fuzzy degenerate jump systems under observer-based event-driven characteristic. IEEE Trans Fuzzy Syst 29(12):3754–3768

    Article  Google Scholar 

  46. Rakkiyappan R, Dharani S, Cao J (2015) Synchronization of neural networks with control packet loss and time-varying delay via stochastic sampled-data controller. IEEE Trans Neural Netw Learn Syst 26(12):3215–3226

    Article  MathSciNet  Google Scholar 

  47. Lakshmanan S, Rihan FA, Rakkiyappan R, Park JH (2014) Stability analysis of the differential genetic regulatory networks model with time-varying delays and Markovian jumping parameters. Nonlinear Anal Hybrid Syst 14:1–15

    Article  MathSciNet  MATH  Google Scholar 

  48. Li F, Xu S, Zhang B (2020) Resilient asynchronous \(H_{\infty }\) control for discrete-time Markov jump singularly perturbed systems based on hidden Markov model. IEEE Trans Syst Man Cybern Syst 50(8):2860–2869

    Google Scholar 

  49. Zhu Y, Zhong Z, Zheng W, Zhou D (2018) HMM-based \(H_\infty \) filtering for discrete-time Markov jump LPV systems over unreliable communication channels. IEEE Trans Syst Man Cybern Syst 48(12):2035–2046

    Article  Google Scholar 

  50. Xing M, Wang Y, Zhuang G, Chen F (2021) Event-based asynchronous and resilient filtering for singular Markov jump LPV systems against deception attacks. Appl Math Comput 403:126176

    MathSciNet  MATH  Google Scholar 

  51. Zhuang G, Xia J, Sun W, Feng J, Ma Q (2021) Asynchronous admissibility and \(H_\infty \) fault detection for delayed implicit Markovian switching systems under hidden Markovian model mechanism. Int J Robust Nonlinear Control 31(15):7261–7279

    Article  MathSciNet  Google Scholar 

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Acknowledgements

The authors would like to thank the Editors and the Referees for carefully reading the paper and for the comments which have helped us to greatly improve the paper. This work was supported by National Natural Science Foundation of China under Grants 62173174, 61773191, 62003154, 61973148; Support Plan for Outstanding Youth Innovation Team in Shandong Higher Education Institutions under Grant 2019KJI010; Natural Science Foundation of Shandong Province for Key Projects under Grant ZR2020KA010; Graduate education high-quality curriculum construction project for Shandong Province under Grant SDYKC20185.

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  1. School of Mathematical Sciences, Liaocheng University, Liaocheng, 252059, Shandong, People’s Republic of China

    Yuexia Yin, Guangming Zhuang, Jianwei Xia & Guoliang Chen

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  1. Yuexia Yin
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Correspondence to Guangming Zhuang.

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Yin, Y., Zhuang, G., Xia, J. et al. Asynchronous \(H_\infty \) Filtering for Singular Markov Jump Neural Networks with Mode-Dependent Time-Varying Delays. Neural Process Lett 54, 5439–5456 (2022). https://doi.org/10.1007/s11063-022-10869-8

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