A New Recursive Least Squares Method with Multiple Forgetting Schemes

We propose a new recursive least squares method drawing inspiration from machine learning ideas.

We propose a recursive least squares method with multiple forgetting schemes to track time-varying model parameters which change with different rates. Our approach hinges on the reformulation of the classic recursive least squares with forgetting scheme as a regularized least squares problem. A simulation study shows the effectiveness of the proposed method. For more details see the paper http://ieeexplore.ieee.org/document/7402726/?arnumber=7402726&tag=1