This paper is concerned with the robust state estimation problem for semi-Markovian switching complex-valued neural networks with quantization effects (QEs). The uncertain parameters are described by the linear fractional uncertainties (LFUs). To enhance the channel utilization and save the communication resources, the measured output is quantized before transmission by a logarithmic quantizer. The purpose of the problem under consideration is to design a full-order state estimator to estimate the complex-valued neuron states. Based on the Lyapunov stability theory, stochastic analysis method, and some improved integral inequalities, sufficient conditions are first derived to guarantee the estimation error system to be globally asymptotically stable in the mean square. Then, the desired state estimator can be directly designed after solving a set of matrix inequalities, which is robust against the LFUs and the QEs. In the end of the paper, one numerical example is provided to illustrate the feasibility and effectiveness of the proposed estimation design scheme. (C) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
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School of Mathematics, Southeast University, Nanjing,210096, ChinaSchool of Mathematics, Southeast University, Nanjing,210096, China
Li, Qiang
Liang, Jinling
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School of Mathematics, Southeast University, Nanjing,210096, ChinaSchool of Mathematics, Southeast University, Nanjing,210096, China
Liang, Jinling
Qu, Hong
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School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu,611731, ChinaSchool of Mathematics, Southeast University, Nanjing,210096, China
机构:
Harbin Inst Technol, Space Control & Inertial Technol Res Ctr, Harbin 150001, Peoples R China
Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, AustraliaHarbin Inst Technol, Space Control & Inertial Technol Res Ctr, Harbin 150001, Peoples R China
Li, Fanbiao
Wu, Ligang
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Harbin Inst Technol, Space Control & Inertial Technol Res Ctr, Harbin 150001, Peoples R ChinaHarbin Inst Technol, Space Control & Inertial Technol Res Ctr, Harbin 150001, Peoples R China
Wu, Ligang
Shi, Peng
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Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia
Victoria Univ, Coll Engn & Sci, Melbourne, Vic 8001, AustraliaHarbin Inst Technol, Space Control & Inertial Technol Res Ctr, Harbin 150001, Peoples R China
Shi, Peng
Lim, Cheng-Chew
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Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, AustraliaHarbin Inst Technol, Space Control & Inertial Technol Res Ctr, Harbin 150001, Peoples R China