Simulation of varying parameter recurrent neural network with application to matrix inversion

DOI10.1016/j.matcom.2021.01.018OpenAlexW3128723704MaRDI QIDQ2661430

Dimitris Gerontitis, Panagiotis Tzekis, Predrag S. Stanimirović, Ratikanta Behera, Jajati Keshari Sahoo

Publication date: 7 April 2021

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2021.01.018

zbMATH Keywords

time-varying systemsrecurrent neural networkfinite-time convergencetime-varying matrix inversion

Mathematics Subject Classification ID

Dynamical systems and ergodic theory (37-XX) Systems theory; control (93-XX)

Related Items (4)

A combined power activation function based convergent factor-variable ZNN model for solving dynamic matrix inversion ⋮ Improved zeroing neural models based on two novel activation functions with exponential behavior ⋮ A noise tolerant parameter-variable zeroing neural network and its applications ⋮ A nonlinear zeroing neural network and its applications on time-varying linear matrix equations solving, electronic circuit currents computing and robotic manipulator trajectory tracking

Uses Software

• Matlab

Cites Work

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• ZNN models for computing matrix inverse based on hyperpower iterative methods
• Recurrent Neural Network Approach Based on the Integral Representation of the Drazin Inverse
• Recurrent Neural Network for Computing Outer Inverse
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