The Nonnegative Zero-Norm Minimization Under Generalized Z-Matrix Measurement
نویسندگان
چکیده
In this paper, we consider the l0 norm minimization problem with linear equation and nonnegativity constraints. By introducing the concept of generalized Z-matrix for a rectangular matrix, we show that this l0 norm minimization with such a kind of measurement matrices and nonnegative observations can be exactly solved via the corresponding lp (0 < p ≤ 1) norm minimization. Moreover, the lower bound of sample number is allowed to be k for recovering the unique k-sparse solution of the underlying l0 norm minimization. A practical application in communications is presented which satisfies the generalized Z-matrix recovery condition.
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عنوان ژورنال:
- J. Optimization Theory and Applications
دوره 160 شماره
صفحات -
تاریخ انتشار 2014