Litcius/Paper detail

<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si40.svg"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="script">H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> state estimation for T-S fuzzy reaction-diffusion delayed neural networks with randomly occurring gain uncertainties and semi-Markov jump parameters

Yamin Liu, Fang Fang, Jianping Zhou, Yajuan Liu

2022Neurocomputing10 citationsDOI

Topics & Concepts

EstimatorComputer scienceArtificial neural networkAlgorithmFuzzy logicApplied mathematicsArtificial intelligenceMachine learningMathematicsStatisticsNeural Networks and ApplicationsMachine Learning and ELMNeural Networks Stability and Synchronization
<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si40.svg"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="script">H</mml:mi></mml:mrow><mml:mrow><mml:mi>∞</mml:mi></mml:mrow></mml:msub></mml:mrow></mml:math> state estimation for T-S fuzzy reaction-diffusion delayed neural networks with randomly occurring gain uncertainties and semi-Markov jump parameters | Litcius