Performance improvement of LMS algorithm using Hopfield model network
説明
An algorithm that improves the adaptation rate of the least-mean-square algorithm and is based on the dynamics of the network in the Hopfield (neural network) model is discussed. The rate of adaptation of the algorithm is shown to be n times as fast as the system of the well-known LMS algorithm with the same control gain, n being the number of iterations for each data sample. The convergence is shown to depend on the gain constant, not on n. Simulations of the convergence behavior of the algorithm are presented. >
収録刊行物
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- [Proceedings] GLOBECOM '90: IEEE Global Telecommunications Conference and Exhibition
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[Proceedings] GLOBECOM '90: IEEE Global Telecommunications Conference and Exhibition 1356-1360, 2002-12-04
IEEE