Abstract:The paper explores in detail the use of dynamic adaptation gain/learning rate (DAG) for improving the performance of gradient type adaptation/learning algorithms. The DAG is an ARMA (poles-zeros) filter embedded in the gradient type adaptation/learning algorithms and generalizes the various improved gradient algorithms available in the literature. After presenting the DAG algorithm and its relation with other algorithms, its design is developed. Strictly Positive Real (SPR) conditions play an important role in… Show more
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