Litcius/Paper detail

On finite-horizon <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si9.svg"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>∞</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> state estimation for discrete-time delayed memristive neural networks under stochastic communication protocol

Hongjian Liu, Zidong Wang, Weiyin Fei, Jiahui Li, Fuad E. Alsaadi

2020Information Sciences24 citationsDOIOpen Access PDF

Topics & Concepts

EstimatorComputer scienceAlgorithmArtificial neural networkApplied mathematicsMathematical optimizationMathematicsArtificial intelligenceStatisticsNeural Networks Stability and SynchronizationDistributed Control Multi-Agent SystemsAdvanced Memory and Neural Computing
On finite-horizon <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si9.svg"> <mml:mrow> <mml:msub> <mml:mrow> <mml:mi>H</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>∞</mml:mi> </mml:mrow> </mml:msub> </mml:mrow> </mml:math> state estimation for discrete-time delayed memristive neural networks under stochastic communication protocol | Litcius