Abstract
This article studies agent–server system identification problems by using a varying infimum gradient descent (VI-GD) algorithm. To efficiently use the GD algorithm for the agent–server with noise, a VI-GD algorithm, which performs a preconditioning matrix before the negative direction of the GD algorithm, is developed. This algorithm can reduce the infimum of the convergence rates without full matrix inversion calculation and can be extended to the systems with ill-conditioned information matrix. Convergence analysis and the comparisons with other methods show the effectiveness of the proposed algorithm. Furthermore, the theoretical results are also verified through simulations.
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