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Explicit shift-invariant dictionary learning
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DOI：10.1109/LSP.2013.2288788.png)
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Abstract
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In this article we give efficient solutions to the construction of structured dictionaries for sparse representations. We study circulant and Toeplitz structures and give fast algorithms based on least squares solutions. We take advantage of explicit circulant structures and we apply the resulting algorithms to shift-invariant learning scenarios. Synthetic experiments and comparisons with state-of-the-art methods show the superiority of the proposed methods.
Keywords:
shift-invariant learning
dictionary learning
sparse representations
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