Abstract
Solving the problem of linear equations is extensively applied in the domains of science and technology, e.g., medicine, economy and so on. Usually, many practical problems in scientific and engineering areas can be converted into a system of linear equations depicted by the formula Mx = b and solved by the corresponding computing methods. In this paper, a nonlinear functions activated noise-tolerant zeroing neural network (NFNTZNN) is presented and exploited for dealing with the time-varying system of linear equations. Differing from the original gradient neural network (GNN) and existing noise-tolerant zeroing neural network (NTZNN), the proposed NFNTZNN model is activated by specially-constructed nonlinear activation functions, and therefore, has the better convergence speed. Simulative results are conducted to verify the efficiency and advantage of the NFNTZNN model for handling the time-varying system of linear equations.
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