Poisson Stability in Symmetrical Impulsive Shunting Inhibitory Cellular Neural Networks with Generalized Piecewise Constant Argument
Akhmet M. Tleubergenova M. Seilova R. Nugayeva Z.
September 2022MDPI
Symmetry
2022#14Issue 9
In the paper, shunting inhibitory cellular neural networks with impulses and the generalized piecewise constant argument are under discussion. The main modeling novelty is that the impulsive part of the systems is symmetrical to the differential part. Moreover, the model depends not only on the continuous time, but also the generalized piecewise constant argument. The process is subdued to Poisson stable inputs, which cause the new type of recurrent signals. The method of included intervals, recently introduced approach of recurrent motions checking, is effectively utilized. The existence and asymptotic properties of the unique Poisson stable motion are investigated. Simulation examples for results are provided. Finally, comparing impulsive shunting inhibitory cellular neural networks with former neural network models, we discuss the significance of the components of our model.
continuous and discontinuous Poisson stable inputs and outputs , continuous and impact activations , generalized piecewise constant argument , impulsive shunting inhibitory cellular neural networks , method of included intervals , symmetry of impulsive and differential parts
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Department of Mathematics, Middle East Technical University, Ankara, 06800, Turkey
Department of Mathematics, Aktobe Regional University, Aktobe, 030000, Kazakhstan
Institute of Information and Computational Technologies CS MES RK, Almaty, 050010, Kazakhstan
Department of Mathematics
Department of Mathematics
Institute of Information and Computational Technologies CS MES RK
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