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M. Wakin, J. Laska, M. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. Kelly, and R. Baraniuk, “An architecture for compressive imaging,” in Proceedings of IEEE Intl. Conference on Image Processing, (IEEE, 2006), pp. 1273–1276.

M. Wakin, J. Laska, M. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. Kelly, and R. Baraniuk, “An architecture for compressive imaging,” in Proceedings of IEEE Intl. Conference on Image Processing, (IEEE, 2006), pp. 1273–1276.

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W. Bajwa, J. Haupt, G. Raz, S. Wright, and R. Nowak, “Toeplitz-structured compressed sensing matrices,” in Proceedings of IEEE Workshop on Statistical Signal Processing, (IEEE, 2007), pp. 294–298.

[CrossRef]

M. Wakin, J. Laska, M. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. Kelly, and R. Baraniuk, “An architecture for compressive imaging,” in Proceedings of IEEE Intl. Conference on Image Processing, (IEEE, 2006), pp. 1273–1276.

S. Kim, K. Koh, M. Lustig, S. Boyd, and D. Gorinevsky, “An interior-point method for large-scale l1-regularized least squares,” IEEE J. Sel. Top. Sig. Proc. 1, 606–617 (2007).

[CrossRef]

S. Kim, K. Koh, M. Lustig, S. Boyd, and D. Gorinevsky, “An interior-point method for large-scale l1-regularized least squares,” IEEE J. Sel. Top. Sig. Proc. 1, 606–617 (2007).

[CrossRef]

M. Wakin, J. Laska, M. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. Kelly, and R. Baraniuk, “An architecture for compressive imaging,” in Proceedings of IEEE Intl. Conference on Image Processing, (IEEE, 2006), pp. 1273–1276.

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S. Kim, K. Koh, M. Lustig, S. Boyd, and D. Gorinevsky, “An interior-point method for large-scale l1-regularized least squares,” IEEE J. Sel. Top. Sig. Proc. 1, 606–617 (2007).

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[CrossRef]
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W. Bajwa, J. Haupt, G. Raz, S. Wright, and R. Nowak, “Toeplitz-structured compressed sensing matrices,” in Proceedings of IEEE Workshop on Statistical Signal Processing, (IEEE, 2007), pp. 294–298.

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B. Liu, F. Sebert, Y. Zou, and L. Ying, “SparseSENSE: randomly-sampled parallel imaging using compressed sensing,” in Proceedings of the 16th Annual Meeting of ISMRM 3154 (2008).

F. Sebert, Y. Zou, and L. Ying, “Toeplitz block matrices in compressed sensing and their applications in imaging,” in Proceedings of IEEE International Conference on Information Technology and Applications in Biomedicine, (IEEE, 2008), pp. 47–50.

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M. Stenner, D. Townsend, and M. Gehm, “Static architecture for compressive motion detection in persistent, pervasive surveillance applications,” in Imaging Systems, OSA Technical Digest Series (Optical Society of America, 2010), paper IMB2.

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M. Wakin, J. Laska, M. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. Kelly, and R. Baraniuk, “An architecture for compressive imaging,” in Proceedings of IEEE Intl. Conference on Image Processing, (IEEE, 2006), pp. 1273–1276.

R. Willett, R. Marcia, and J. Nichols, “Compressed sensing for practical optical imaging systems: a tutorial,” Opt. Eng. 50, 072601 (2011).

[CrossRef]

W. Bajwa, J. Haupt, G. Raz, S. Wright, and R. Nowak, “Toeplitz-structured compressed sensing matrices,” in Proceedings of IEEE Workshop on Statistical Signal Processing, (IEEE, 2007), pp. 294–298.

[CrossRef]

B. Liu, F. Sebert, Y. Zou, and L. Ying, “SparseSENSE: randomly-sampled parallel imaging using compressed sensing,” in Proceedings of the 16th Annual Meeting of ISMRM 3154 (2008).

F. Sebert, Y. Zou, and L. Ying, “Toeplitz block matrices in compressed sensing and their applications in imaging,” in Proceedings of IEEE International Conference on Information Technology and Applications in Biomedicine, (IEEE, 2008), pp. 47–50.

[CrossRef]

B. Liu, F. Sebert, Y. Zou, and L. Ying, “SparseSENSE: randomly-sampled parallel imaging using compressed sensing,” in Proceedings of the 16th Annual Meeting of ISMRM 3154 (2008).

F. Sebert, Y. Zou, and L. Ying, “Toeplitz block matrices in compressed sensing and their applications in imaging,” in Proceedings of IEEE International Conference on Information Technology and Applications in Biomedicine, (IEEE, 2008), pp. 47–50.

[CrossRef]

S. Kim, K. Koh, M. Lustig, S. Boyd, and D. Gorinevsky, “An interior-point method for large-scale l1-regularized least squares,” IEEE J. Sel. Top. Sig. Proc. 1, 606–617 (2007).

[CrossRef]

J. Tropp, “Just relax: Convex programming methods for identifying sparse signals in noise,” IEEE Trans. Inf. Theory 52, 1030–1051 (2006).

[CrossRef]

M. Lustig, D. Donoho, and J. Pauly, “Sparse MRI: The application of compressed sensing for rapid MR imaging,” Magn. Reson. Med. 58, 1182–1195 (2007).

[CrossRef]
[PubMed]

R. Willett, R. Marcia, and J. Nichols, “Compressed sensing for practical optical imaging systems: a tutorial,” Opt. Eng. 50, 072601 (2011).

[CrossRef]

B. Liu, F. Sebert, Y. Zou, and L. Ying, “SparseSENSE: randomly-sampled parallel imaging using compressed sensing,” in Proceedings of the 16th Annual Meeting of ISMRM 3154 (2008).

J. Romberg, “Compressive sensing by random convolution,” SIAM J. Imaging Sci. 2, 1098–1128 (2009).

[CrossRef]

F. Sebert, Y. Zou, and L. Ying, “Toeplitz block matrices in compressed sensing and their applications in imaging,” in Proceedings of IEEE International Conference on Information Technology and Applications in Biomedicine, (IEEE, 2008), pp. 47–50.

[CrossRef]

M. Wakin, J. Laska, M. Duarte, D. Baron, S. Sarvotham, D. Takhar, K. Kelly, and R. Baraniuk, “An architecture for compressive imaging,” in Proceedings of IEEE Intl. Conference on Image Processing, (IEEE, 2006), pp. 1273–1276.

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M. Stenner, D. Townsend, and M. Gehm, “Static architecture for compressive motion detection in persistent, pervasive surveillance applications,” in Imaging Systems, OSA Technical Digest Series (Optical Society of America, 2010), paper IMB2.