Complexity reduction in compressive sensing using Hirschman uncertainty structured random matrices
暂无分享,去创建一个
[1] Victor E. DeBrunner,et al. Resolution in time-frequency , 1999, IEEE Trans. Signal Process..
[2] V. DeBrunner,et al. Entropy-based uncertainty measures for L/sup 2/(/spl Ropf//sup n/), /spl lscr//sup 2/(/spl Zopf/), and /spl lscr//sup 2/(/spl Zopf//N/spl Zopf/) with a Hirschman optimal transform for /spl lscr//sup 2/(/spl Zopf//N/spl Zopf/) , 2005, IEEE Transactions on Signal Processing.
[3] Holger Rauhut,et al. The Gelfand widths of lp-balls for 0p<=1 , 2010, J. Complex..
[4] R.G. Baraniuk,et al. Compressive Sensing [Lecture Notes] , 2007, IEEE Signal Processing Magazine.
[5] Xiaoming Huo,et al. Uncertainty principles and ideal atomic decomposition , 2001, IEEE Trans. Inf. Theory.
[6] Stéphane Mallat,et al. Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..
[7] Victor E. DeBrunner,et al. The optimal solutions to the continuous and discrete-time versions of the Hirschman uncertainty principle , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).