Quantized asynchronous dissipative state estimation of jumping neural networks subject to occurring randomly sensor saturations

In this work, we study the quantized asynchronous dissipative state estimation issue for Markov jumping neural networks subject to randomly occurring sensor saturations. The network-induced phenomena (e.g. the sensor saturations and the signal quantization) are assumed to be occurring randomly. A st...

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Vydané v:	Neurocomputing (Amsterdam) Ročník 291; s. 207 - 214
Hlavní autori:	Men, Yunzhe, Huang, Xia, Wang, Zhen, Shen, Hao, Chen, Bo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 24.05.2018
Predmet:	Asynchronous dissipative state estimation Jumping neural networks Sensor saturations Signal quantization Sensor saturations Jumping neural networks Asynchronous dissipative state estimation Signal quantization
ISSN:	0925-2312, 1872-8286
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