摘要

We introduce the concept of average best m-term approximation widths with respect to a probability measure on the unit ball or the unit sphere of . We estimate these quantities for the embedding with 0 < pa parts per thousand currency signqa parts per thousand currency signa for the normalized cone and surface measure. Furthermore, we consider certain tensor product weights and show that a typical vector with respect to such a measure exhibits a strong compressible (i.e., nearly sparse) structure. This measure may therefore be used as a random model for sparse signals.

  • 出版日期2012-8

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