High-Dimensional Matched Subspace Detection When Data are Missing

Understand

We consider the problem of deciding whether a highly incomplete signal lies within a given subspace.

• This problem, Matched Subspace Detection, is a classical, well-studied problem when the signal is completely observed.
• High- dimensional testing problems in which it may be prohibitive or impossible to obtain a complete observation motivate this work.
• The signal is represented as a vector in R^n, but we only observe m << n of its elements.