\(H_\infty\) filtering for nonlinear systems via neural networks
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Publication:602671
DOI10.1016/j.jfranklin.2009.11.006zbMath1201.93124OpenAlexW2075573259MaRDI QIDQ602671
Xiaoli Luan, Fei Liu, Peng Shi
Publication date: 5 November 2010
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jfranklin.2009.11.006
Related Items (9)
Stochastic input-to-state stability and \(H_{\infty}\) filtering for a class of stochastic nonlinear systems ⋮ Unscented H-infinity filtering based simultaneous localization and mapping with evolutionary resampling ⋮ \(H_\infty\) filter design for nonlinear parameter-varying systems with quantized measurements ⋮ A new approach to \(H_{\infty }\) filtering for linear time-delay systems ⋮ Outlier-robust Kalman filters with mixture correntropy ⋮ Event‐triggered quantized L2−L∞$$ {\mathfrak{L}}_2-{\mathfrak{L}}_{\infty } $$ filtering for neural networks under denial‐of‐service attacks ⋮ A delay-derivative-dependent approach to robust \(H^\infty\) filter design for uncertain systems with time-varying distributed delays ⋮ Random-valued impulse noise removal based on component-wise noise detector with auto-tuning function and vector median interpolation ⋮ Stochastic stability analysis of piecewise homogeneous Markovian jump neural networks with mixed time-delays
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