Subspace tracking using a constrained hyperbolic URV decomposition
نویسنده
چکیده
Fast adaptive subspace estimation plays an increasingly important role in modern signal processing. It forms the key ingredient in many sensor array signal processing algorithms, system identification, and several recently derived blind signal separation and equalization algorithms. The generic subspace estimation problem in these applications might be stated as follows. Suppose that we are given a data matrix X : m×n, measured column-by-column, that satisfies the model X = X̃ + Ñ, where X̃ is a low rank matrix and Ñ is a disturbance. Knowing only X, we can try to estimate X̃ by solving
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