Generalized adaptive weighted recursive least squares dictionary learning
We generalize the recursive least squares dictionary learning algorithm. Our algorithm GAW-RLS introduces a correction weight for the arrival data. Controls the relative consistency between arrival data and existing dictionary. This improves the convergence of algorithm, MSE of sparse representation. This makes the algorithm more robust in dealing with outliers in the training data.
adaptive weighting recursive least squares dictionary learning sparse signal representation