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Motivated by the advantages achieved by implicit analogue net for solvingonline linear equations, a novel implicit neural model is designed based onconventional explicit gradient neural networks in this letter by introducing apositive-definite mass matrix. In addition to taking the advantages of theimplicit neural dynamics, the proposed implicit gradient neural networks canstill achieve globally exponential convergence to the unique theoreticalsolution of linear equations and also global stability even under no-solutionand multi-solution situations. Simulative results verify theoreticalconvergence analysis on the proposed neural dynamics.

Implicit Gradient Neural Networks with a Positive-Definite Mass Matrix for Online Linear Equations Solving