Y. Chi, L. L. Scharf, A. Pezeshki, and A. R. Calderbank, “Sensitivity to basis mismatch in compressed sensing,” IEEE Trans. Signal Process. 59, 2182–2195 (2011).

[CrossRef]

J. D. Blanchard, C. Cartis, and J. Tanner, “Compressed sensing: how sharp is the restricted isometry property,” SIAM Rev. 53, 105–125 (2011).

[CrossRef]

J. M. Nichols and F. Bucholtz, “Beating Nyquist with light: a compressively sampled photonic link,” Opt. Express 19, 7339–7348 (2011).

[CrossRef]

J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, “Beyond Nyquist: efficient sampling of sparse bandlimited signals,” IEEE Trans. Inf. Theory 56, 520–544 (2010).

[CrossRef]

D. L. Donoho and J. Tanner, “Exponential bounds implying construction of compressed sensing matrices, error-correcting codes, and neighborly polytopes by random sampling,” IEEE Trans. Inf. Theory 56, 2002–2016 (2010).

[CrossRef]

D. L. Donoho and J. Tanner, “Precise undersampling theorems,” Proc. IEEE 98, 913–924 (2010).

[CrossRef]

M. Mishali and Y. C. Eldar, “From theory to practice: sub-Nyquist sampling of sparse wideband analog signals,” IEEE J. Sel. Top. Signal Process. 4, 375–391 (2010).

[CrossRef]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51, 34–81 (2009).

[CrossRef]

E. J. Candes, “The restricted isometry property and its implications for compressed sensing,” C. R. Math. 346, 589–592 (2008).

[CrossRef]

J. Romberg, “Imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 14–20 (2008).

[CrossRef]

E. J. Candes and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).

[CrossRef]

M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, “Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems,” IEEE J. Sel. Top. Signal Process. 1, 586–597 (2007).

[CrossRef]

D. L. Donoho, M. Elad, and V. N. Temlyakov, “Stable recovery of sparse overcomplete representations in the presence of noise,” IEEE Trans. Inf. Theory 52, 6–18 (2006).

[CrossRef]

E. J. Candes and T. Tao, “Near-optimal signal recovery from random projections: universal encoding strategies?” IEEE Trans. Inf. Theory 52, 5406–5425 (2006).

[CrossRef]

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006).

[CrossRef]

E. J. Candes and T. Tao, “Decoding by linear programming,” IEEE Trans. Inf. Theory 51, 4203–4215 (2005).

[CrossRef]

C. E. Shannon, “Communication in the presence of noise,” Proc. IEEE 86, 447–457 (1998), reprinted from Proc. IRE 37, 10–21 (1949).

[CrossRef]

A. Harms, W. U. Bajwa, and R. Calderbank, “Beating Nyquist through correlations: a constrained random demodulator for sampling of sparse bandlimited signals,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2011), pp. 5968–5971.

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, “Beyond Nyquist: efficient sampling of sparse bandlimited signals,” IEEE Trans. Inf. Theory 56, 520–544 (2010).

[CrossRef]

R. G. Baraniuk, “Compressive sensing,” IEEE Signal Process. Mag.24(4), 118–124 (2007).

[CrossRef]

J. D. Blanchard, C. Cartis, and J. Tanner, “Compressed sensing: how sharp is the restricted isometry property,” SIAM Rev. 53, 105–125 (2011).

[CrossRef]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51, 34–81 (2009).

[CrossRef]

Y. Chi, L. L. Scharf, A. Pezeshki, and A. R. Calderbank, “Sensitivity to basis mismatch in compressed sensing,” IEEE Trans. Signal Process. 59, 2182–2195 (2011).

[CrossRef]

A. Harms, W. U. Bajwa, and R. Calderbank, “Beating Nyquist through correlations: a constrained random demodulator for sampling of sparse bandlimited signals,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2011), pp. 5968–5971.

E. J. Candes, “The restricted isometry property and its implications for compressed sensing,” C. R. Math. 346, 589–592 (2008).

[CrossRef]

E. J. Candes and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).

[CrossRef]

E. J. Candes and T. Tao, “Near-optimal signal recovery from random projections: universal encoding strategies?” IEEE Trans. Inf. Theory 52, 5406–5425 (2006).

[CrossRef]

E. J. Candes and T. Tao, “Decoding by linear programming,” IEEE Trans. Inf. Theory 51, 4203–4215 (2005).

[CrossRef]

J. D. Blanchard, C. Cartis, and J. Tanner, “Compressed sensing: how sharp is the restricted isometry property,” SIAM Rev. 53, 105–125 (2011).

[CrossRef]

Y. Chi, L. L. Scharf, A. Pezeshki, and A. R. Calderbank, “Sensitivity to basis mismatch in compressed sensing,” IEEE Trans. Signal Process. 59, 2182–2195 (2011).

[CrossRef]

D. L. Donoho and J. Tanner, “Precise undersampling theorems,” Proc. IEEE 98, 913–924 (2010).

[CrossRef]

D. L. Donoho and J. Tanner, “Exponential bounds implying construction of compressed sensing matrices, error-correcting codes, and neighborly polytopes by random sampling,” IEEE Trans. Inf. Theory 56, 2002–2016 (2010).

[CrossRef]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51, 34–81 (2009).

[CrossRef]

D. L. Donoho, M. Elad, and V. N. Temlyakov, “Stable recovery of sparse overcomplete representations in the presence of noise,” IEEE Trans. Inf. Theory 52, 6–18 (2006).

[CrossRef]

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006).

[CrossRef]

J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, “Beyond Nyquist: efficient sampling of sparse bandlimited signals,” IEEE Trans. Inf. Theory 56, 520–544 (2010).

[CrossRef]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51, 34–81 (2009).

[CrossRef]

D. L. Donoho, M. Elad, and V. N. Temlyakov, “Stable recovery of sparse overcomplete representations in the presence of noise,” IEEE Trans. Inf. Theory 52, 6–18 (2006).

[CrossRef]

R. Rubinstein, M. Zibulevsky, and M. Elad, “Efficient implementation of the K-SVD algorithm using batch orthogonal matching pursuit,” CS Tech. Rep. (Technion–Israel Institute of Technology, 2008).

M. Mishali and Y. C. Eldar, “From theory to practice: sub-Nyquist sampling of sparse wideband analog signals,” IEEE J. Sel. Top. Signal Process. 4, 375–391 (2010).

[CrossRef]

M. Mishali and Y. C. Eldar, “Xampling: analog data compression,” in Proceedings of the 2010 Data Compression Conference (IEEE, 2010), pp. 366–375.

M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, “Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems,” IEEE J. Sel. Top. Signal Process. 1, 586–597 (2007).

[CrossRef]

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

A. Harms, W. U. Bajwa, and R. Calderbank, “Beating Nyquist through correlations: a constrained random demodulator for sampling of sparse bandlimited signals,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2011), pp. 5968–5971.

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, “Beyond Nyquist: efficient sampling of sparse bandlimited signals,” IEEE Trans. Inf. Theory 56, 520–544 (2010).

[CrossRef]

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

M. Mishali and Y. C. Eldar, “From theory to practice: sub-Nyquist sampling of sparse wideband analog signals,” IEEE J. Sel. Top. Signal Process. 4, 375–391 (2010).

[CrossRef]

M. Mishali and Y. C. Eldar, “Xampling: analog data compression,” in Proceedings of the 2010 Data Compression Conference (IEEE, 2010), pp. 366–375.

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, “Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems,” IEEE J. Sel. Top. Signal Process. 1, 586–597 (2007).

[CrossRef]

Y. Chi, L. L. Scharf, A. Pezeshki, and A. R. Calderbank, “Sensitivity to basis mismatch in compressed sensing,” IEEE Trans. Signal Process. 59, 2182–2195 (2011).

[CrossRef]

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

J. Romberg, “Imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 14–20 (2008).

[CrossRef]

J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, “Beyond Nyquist: efficient sampling of sparse bandlimited signals,” IEEE Trans. Inf. Theory 56, 520–544 (2010).

[CrossRef]

R. Rubinstein, M. Zibulevsky, and M. Elad, “Efficient implementation of the K-SVD algorithm using batch orthogonal matching pursuit,” CS Tech. Rep. (Technion–Israel Institute of Technology, 2008).

Y. Chi, L. L. Scharf, A. Pezeshki, and A. R. Calderbank, “Sensitivity to basis mismatch in compressed sensing,” IEEE Trans. Signal Process. 59, 2182–2195 (2011).

[CrossRef]

C. E. Shannon, “Communication in the presence of noise,” Proc. IEEE 86, 447–457 (1998), reprinted from Proc. IRE 37, 10–21 (1949).

[CrossRef]

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

J. D. Blanchard, C. Cartis, and J. Tanner, “Compressed sensing: how sharp is the restricted isometry property,” SIAM Rev. 53, 105–125 (2011).

[CrossRef]

D. L. Donoho and J. Tanner, “Precise undersampling theorems,” Proc. IEEE 98, 913–924 (2010).

[CrossRef]

D. L. Donoho and J. Tanner, “Exponential bounds implying construction of compressed sensing matrices, error-correcting codes, and neighborly polytopes by random sampling,” IEEE Trans. Inf. Theory 56, 2002–2016 (2010).

[CrossRef]

E. J. Candes and T. Tao, “Near-optimal signal recovery from random projections: universal encoding strategies?” IEEE Trans. Inf. Theory 52, 5406–5425 (2006).

[CrossRef]

E. J. Candes and T. Tao, “Decoding by linear programming,” IEEE Trans. Inf. Theory 51, 4203–4215 (2005).

[CrossRef]

D. L. Donoho, M. Elad, and V. N. Temlyakov, “Stable recovery of sparse overcomplete representations in the presence of noise,” IEEE Trans. Inf. Theory 52, 6–18 (2006).

[CrossRef]

J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, “Beyond Nyquist: efficient sampling of sparse bandlimited signals,” IEEE Trans. Inf. Theory 56, 520–544 (2010).

[CrossRef]

E. J. Candes and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).

[CrossRef]

M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, “Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems,” IEEE J. Sel. Top. Signal Process. 1, 586–597 (2007).

[CrossRef]

R. Rubinstein, M. Zibulevsky, and M. Elad, “Efficient implementation of the K-SVD algorithm using batch orthogonal matching pursuit,” CS Tech. Rep. (Technion–Israel Institute of Technology, 2008).

E. J. Candes, “The restricted isometry property and its implications for compressed sensing,” C. R. Math. 346, 589–592 (2008).

[CrossRef]

M. Mishali and Y. C. Eldar, “From theory to practice: sub-Nyquist sampling of sparse wideband analog signals,” IEEE J. Sel. Top. Signal Process. 4, 375–391 (2010).

[CrossRef]

M. A. T. Figueiredo, R. D. Nowak, and S. J. Wright, “Gradient projection for sparse reconstruction: application to compressed sensing and other inverse problems,” IEEE J. Sel. Top. Signal Process. 1, 586–597 (2007).

[CrossRef]

J. Romberg, “Imaging via compressive sampling,” IEEE Signal Process. Mag. 25(2), 14–20 (2008).

[CrossRef]

E. J. Candes and M. B. Wakin, “An introduction to compressive sampling,” IEEE Signal Process. Mag. 25(2), 21–30 (2008).

[CrossRef]

D. L. Donoho and J. Tanner, “Exponential bounds implying construction of compressed sensing matrices, error-correcting codes, and neighborly polytopes by random sampling,” IEEE Trans. Inf. Theory 56, 2002–2016 (2010).

[CrossRef]

D. L. Donoho, M. Elad, and V. N. Temlyakov, “Stable recovery of sparse overcomplete representations in the presence of noise,” IEEE Trans. Inf. Theory 52, 6–18 (2006).

[CrossRef]

E. J. Candes and T. Tao, “Near-optimal signal recovery from random projections: universal encoding strategies?” IEEE Trans. Inf. Theory 52, 5406–5425 (2006).

[CrossRef]

D. L. Donoho, “Compressed sensing,” IEEE Trans. Inf. Theory 52, 1289–1306 (2006).

[CrossRef]

J. A. Tropp, J. N. Laska, M. F. Duarte, J. K. Romberg, and R. G. Baraniuk, “Beyond Nyquist: efficient sampling of sparse bandlimited signals,” IEEE Trans. Inf. Theory 56, 520–544 (2010).

[CrossRef]

E. J. Candes and T. Tao, “Decoding by linear programming,” IEEE Trans. Inf. Theory 51, 4203–4215 (2005).

[CrossRef]

Y. Chi, L. L. Scharf, A. Pezeshki, and A. R. Calderbank, “Sensitivity to basis mismatch in compressed sensing,” IEEE Trans. Signal Process. 59, 2182–2195 (2011).

[CrossRef]

D. L. Donoho and J. Tanner, “Precise undersampling theorems,” Proc. IEEE 98, 913–924 (2010).

[CrossRef]

C. E. Shannon, “Communication in the presence of noise,” Proc. IEEE 86, 447–457 (1998), reprinted from Proc. IRE 37, 10–21 (1949).

[CrossRef]

J. D. Blanchard, C. Cartis, and J. Tanner, “Compressed sensing: how sharp is the restricted isometry property,” SIAM Rev. 53, 105–125 (2011).

[CrossRef]

A. M. Bruckstein, D. L. Donoho, and M. Elad, “From sparse solutions of systems of equations to sparse modeling of signals and images,” SIAM Rev. 51, 34–81 (2009).

[CrossRef]

S. Pfetsch, T. Ragheb, J. Laska, H. Nejati, A. Gilbert, M. Strauss, R. Baraniuk, and Y. Massoud, “On the feasibility of hardware implementation of sub-Nyquist random-sampling based analog-to-information conversion,” in Proceedings of the IEEE International Symposium on Circuits and Systems (IEEE,2008), pp. 1480–1483.

M. Mishali and Y. C. Eldar, “Xampling: analog data compression,” in Proceedings of the 2010 Data Compression Conference (IEEE, 2010), pp. 366–375.

R. G. Baraniuk, “Compressive sensing,” IEEE Signal Process. Mag.24(4), 118–124 (2007).

[CrossRef]

R. Rubinstein, M. Zibulevsky, and M. Elad, “Efficient implementation of the K-SVD algorithm using batch orthogonal matching pursuit,” CS Tech. Rep. (Technion–Israel Institute of Technology, 2008).

A. Harms, W. U. Bajwa, and R. Calderbank, “Beating Nyquist through correlations: a constrained random demodulator for sampling of sparse bandlimited signals,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (IEEE, 2011), pp. 5968–5971.