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Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
Published on: March 9, 2019
Preassigned-time synchronization for complex-valued memristive neural networks with reaction-diffusion terms and
Hongliang Liu1, Jun Cheng2, Jinde Cao3
1School of Mathematics and Physics, University of South China, Hengyang, 421001, PR China.
Abstract:
This study addresses the preassigned-time synchronization for complex-valued memristive neural networks with reaction-diffusion terms and Markov parameters. Employing a preassigned-time stable control strategy, two distinct controllers with varying power exponent parameters are designed to ensure that synchronization can be achieved within a predefined time frame. Unlike existing finite/fixed-time results, a priori specification of the settling time is addressed. Furthermore, Green's formula and boundary conditions are efficiently applied to overcome potential symmetry loss. Additionally, the activation function's constraint range is more lenient compared to existing constraints. Finally, the effectiveness of the presented methods are demonstrated through two examples.
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