Compressive sensing and filter-bank signal models

A compressible signal can often be modeled as a sum of outputs of subband filters of a synthesis filter bank. This model allows one to find compressive sampling schemes, whereby the original continuous signal can directly be acquired by sampling at a very low (sub-Nyquist) rate. This paper revisits this result from the view point of filter bank theory. This is motivated by recent work by Mishali and Eldar on the so-called Xampling techniques for compressible signals. The viewpoint presented here emphasizes the simplicity and directness of the compressive sensing idea and also places in evidence the framework which can be used to formulate optimal compressive sampling problems.

[1]  Yonina C. Eldar,et al.  Xampling: Signal Acquisition and Processing in Union of Subspaces , 2009, IEEE Transactions on Signal Processing.

[2]  Thierry Blu,et al.  Sampling signals with finite rate of innovation , 2002, IEEE Trans. Signal Process..

[3]  R.G. Baraniuk,et al.  Compressive Sensing [Lecture Notes] , 2007, IEEE Signal Processing Magazine.

[4]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[5]  Richard G. Baraniuk,et al.  Compressive Sensing , 2008, Computer Vision, A Reference Guide.

[6]  Emmanuel J. Candès,et al.  Decoding by linear programming , 2005, IEEE Transactions on Information Theory.

[7]  P. P. Vaidyanathan,et al.  Signal Processing and Optimization for Transceiver Systems , 2010 .

[8]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[9]  Martin J. Wainwright,et al.  Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$ -Constrained Quadratic Programming (Lasso) , 2009, IEEE Transactions on Information Theory.

[10]  P. P. Vaidyanathan,et al.  Some results in the theory of crosstalk-free transmultiplexers , 1991, IEEE Trans. Signal Process..

[11]  Martin Vetterli,et al.  Perfect transmultiplexers , 1986, ICASSP '86. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[12]  Joel A. Tropp,et al.  Greed is good: algorithmic results for sparse approximation , 2004, IEEE Transactions on Information Theory.

[13]  P. Vaidyanathan Multirate Systems And Filter Banks , 1992 .

[14]  Yonina C. Eldar Compressed Sensing of Analog Signals in Shift-Invariant Spaces , 2008, IEEE Transactions on Signal Processing.