Finite-Time State Estimation for Coupled Markovian Neural Networks With Sensor Nonlinearities

• Published in: IEEE transaction on neural networks and learning systems Vol. 28; no. 3; pp. 630 - 638
• Main Authors: Wang, Zhuo, Xu, Yong, Lu, Renquan, Peng, Hui
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Coupled Markovian neural networks; Error analysis; Estimation error; Linear matrix inequalities; Markov analysis; Markov chains; Markov processes; Mathematical analysis; Matrix methods; Neural networks; sensor nonlinearity; Stability analysis; State estimation; stochastic finite-time boundedness; stochastic finite-time stability; Transition probabilities; Yttrium

This paper investigates the issue of finite-time state estimation for coupled Markovian neural networks subject to sensor nonlinearities, where the Markov chain with partially unknown transition probabilities is considered. A Luenberger-type state estimator is proposed based on incomplete measuremen...