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An Array Recursive Least-Squares Algorithm With Generic Nonfading Regularization Matrix
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DOI：10.1109/LSP.2010.2083652.png)
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Abstract
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We present a novel array RLS algorithm with forgetting factor that circumvents the problem of fading regularization, inherent to the standard exponentially-weighted RLS, by allowing for time-varying regularization matrices with generic structure. Simulations in finite precision show the algorithm's superiority as compared to alternative algorithms in the context of adaptive beamforming.
Keywords:
Arrays
Equations
Array signal processing
Complexity theory
Robustness
Eigenvalues and eigenfunctions
RLS
Array forms
regularization
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