广义绝对值方程的免逆神经网络方法
An inverse-free neural network methods for generalized absolute value equations
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摘要: 基于广义绝对值方程的解与广义线性互补问题的解的关系,建立了求解广义绝对值方程的免逆神经网络模型,给出了其稳定性和误差分析,并通过数值算例验证了该方法的有效性.Abstract: Based on the relationship between the solutions of the generalized absolute value equation and the generalized linear complementarity problem, we establishes an inverse-free neural network model for solving the generalized absolute value equation, the stability and error analysis of the model are provided. Its effectiveness is verified through numerical examples.
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