Litcius/Paper detail

Non-fragile mixed passive and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:msub><mml:mi mathvariant="bold-script">H</mml:mi><mml:mi>∞</mml:mi></mml:msub></mml:math> state estimation for singularly perturbed neural networks with semi-Markov jumping parameters

Hao Shen, Yuan Wang, Jianwei Xia, Jinde Cao, Xiangyong Chen

2020Journal of the Franklin Institute32 citationsDOI

Topics & Concepts

EstimatorArtificial neural networkApplied mathematicsComputer scienceAlgorithmFunction (biology)MathematicsArtificial intelligenceStatisticsBiologyEvolutionary biologyStability and Control of Uncertain SystemsNeural Networks Stability and SynchronizationAdaptive Control of Nonlinear Systems
Non-fragile mixed passive and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:msub><mml:mi mathvariant="bold-script">H</mml:mi><mml:mi>∞</mml:mi></mml:msub></mml:math> state estimation for singularly perturbed neural networks with semi-Markov jumping parameters | Litcius