Identification of Matrices Having a Sparse Representation

Pfander, G. E.; Rauhut, H. und Tanner, J. (2008): Identification of Matrices Having a Sparse Representation. In: IEEE Transactions on Signal Processing, Vol. 56, No. 11: pp. 5376-5388

Abstract

We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary. Connections with sparse signal recovery allows for the use of efficient reconstruction techniques such as basis pursuit. Of particular interest is the dictionary of time-frequency shift matrices and its role for channel estimation and identification in communications engineering. We present recovery results for basis pursuit with the time-frequency shift dictionary and various dictionaries of random matrices.

• Item Type: Journal article
• Faculties: Mathematics, Computer Science and Statistics > Mathematics > Chair of Mathematics of Information Processing
• Subjects: 500 Science > 510 Mathematics
• ISSN: 1053-587X
• Language: English