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87. Assawinchaichote W, Nguang SK, Shi P (2007) Robust H ∞ fuzzy filter design for uncertain
nonlinear singularly perturbed systems with Markovian jumps: an LMI approach. Inf Sci
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88. Wu L, Shi P, Gao H, Wang C (2008) H ∞ filtering for 2D Markovian jump systems. Automatica
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of linear state-space model. Automatica 85:91–99
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apriori information on initial conditions. IEEE Trans Autom Control 62(2):882–887
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175
86. Xu S, Chen T, Lam J (2003) Robust H ∞ filtering for uncertain Markovian jump systems with
mode-dependent time delays. IEEE Trans Autom Control 48(5):900–907
87. Assawinchaichote W, Nguang SK, Shi P (2007) Robust H ∞ fuzzy filter design for uncertain
nonlinear singularly perturbed systems with Markovian jumps: an LMI approach. Inf Sci
177(7):1699–1714
88. Wu L, Shi P, Gao H, Wang C (2008) H ∞ filtering for 2D Markovian jump systems. Automatica
44(7):1849–1858
89. Zhang L, Boukas EK (2009) Mode-dependent H ∞ filtering for discrete-time Markovian jump
linear systems with partly unknown transition probabilities. Automatica 45(6):1462–1467
90. He S, Liu F (2010) Robust peak-to-peak filtering for Markov jump systems. Signal Process
90(2):513–522
91. He S, Song J, Liu F (2014) Unbiased estimation of Markov jump systems with distributed
delays. Signal Process 100:85–92
92. He S (2014) Fault estimation for T-S fuzzy Markovian jumping systems based on the adaptive
observer. Int J Control Autom Syst 12(5):977–985
93. Wu Z, Shi P, Su H, Chu J (2014) Asynchronous L2-L filtering for discrete-time stochastic
Markov jump systems with randomly occurred sensor nonlinearities. Automatica 50(1):180–
186
94. Zhang L, Zhu Y, Zheng WX (2015) Energy-to-peak state estimation for Markov jump RNNs
with time-varying delays via nonsynchronous filter with nonstationary mode transitions. IEEE
Trans Neural Netw Learn Syst 26(10):2346–2356
95. Tian E, Wong WK, Yue D, Yang TC (2015) H ∞ Filtering for discrete-time switched systems
with known sojourn probabilities. IEEE Trans Autom Control 60(9):2446–2451
96. Ren H, Zong G (2017) Robust input-output finite-time filtering for uncertain Markovian jump
nonlinear systems with partially known transition probabilities. Int J Adapt Control Signal
Process 31(10):1437–1455
97. Cheng J, Park JuH, Cao J, Zhang D (2018) Quantized H ∞ filtering for switched linear
parameter-varying systems with sojourn probabilities and unreliable communication channels. Inf Sci 466:289–302
98. Shen H, Huo S, Cao J, Huang T (2019) Generalized state estimation for Markovian coupled networks under round-robin protocol and redundant channels. IEEE Trans Cybern
49(4):1292–1301
99. Shen H, Zhu Y, Zhang L, Park JuH (2017) Extended dissipative state estimation for Markov
jump neural networks with unreliable links. IEEE Trans Neural Netw Learn Syst 28(2):346–
358
100. Liu J, Wei L, Cao J, Fei S (2019) Hybrid-driven H ∞ filter design for T-S fuzzy systems with
quantization. Nonlinear Anal Hybrid Syst 31:135–152
101. Xu Y, Lu R, Shi P, Li H, Xie S (2017) Finite-time distributed state estimation over sensor
networks with Round-Robin protocol and fading channels. IEEE Trans Cybern 48(1):336–345
102. Xu Y, Lu R, Shi P, Tao J, Xie S (2017) Robust estimation for neural networks with randomly
occurring distributed delays and Markovian jump coupling. IEEE Trans Neural Netw Learn
Syst 28(2):268–277
103. Xu Y, Lu R, Peng H, Xie K, Xue A (2017) Asynchronous dissipative state estimation for
stochastic complex networks with quantized jumping coupling and uncertain measurements.
IEEE Trans Neural Netw Learn Syst 28(2):268–277
104. Zhao S, Huang B, Shmaliy YS (2017) Bayesian state estimation on finite horizons: the case
of linear state-space model. Automatica 85:91–99
105. Zhao S, Huang B, Liu F (2017) Linear optimal unbiased filter for time-variant systems without
apriori information on initial conditions. IEEE Trans Autom Control 62(2):882–887
106. Zhao S, Shmaliy YS, Huang B, Liu F (2015) Minimum variance unbiased FIR filter for
discrete time-variant systems. Automatica 53:355–361
107. Zhao S, Shmaliy YS, Liu F (2016) Fast Kalman-like optimal unbiased FIR filtering with
applications. IEEE Trans Signal Process 64(9):2284–2297