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Donoho, D. L. Compressed sensing. Information Theory, IEEE Transactions on, 52(4), pp,1289-1306,2006.10.1109/TIT.2006.871582Search in Google Scholar
Candès E,Romberg J,Tao T. Robust uncertainty principles:exact signal recognition from highly incomplete frequency information[J]. IEEE Trans.Info.Theory,52(2), pp.489-509, 2006.10.1109/TIT.2005.862083Search in Google Scholar
Lee S R. A Coarse-to-Fine Approach for Remote-Sensing Image Registration Based on a Local Method[J]. International Journal on Smart Sensing & Intelligent Systems, 3(4), 2010.10.21307/ijssis-2017-416Search in Google Scholar
Condat, L.. A primal–dual splitting method for convex optimization involving Lipschitzian, proximable and linear composite terms. Journal of Optimization Theory and Applications, 158(2), 460-479,2013.10.1007/s10957-012-0245-9Search in Google Scholar
Harmany, Z., Thompson, D., Willett, R., & Marcia, R. F. (2010, September). Gradient projection for linearly constrained convex optimization in sparse signal recovery. In Image Processing (ICIP), 2010 17th IEEE International Conference on (pp. 3361-3364). IEEE.10.1109/ICIP.2010.5652815Search in Google Scholar
Iwen, M. A. (2009, March). Simple deterministically constructible rip matrices with sublinear fourier sampling requirements. In Information Sciences and Systems, 2009. CISS 2009. 43rd Annual Conference on (pp. 870-875). IEEE.10.1109/CISS.2009.5054839Search in Google Scholar
Zhang, T. Sparse recovery with orthogonal matching pursuit under RIP. Information Theory, IEEE Transactions on, 57(9),pp. 6215-6221,2011.Search in Google Scholar
Zhang, Y. Theory of Compressive Sensing via ℓ 1-Minimization: a Non-RIP Analysis and Extensions. Journal of the Operations Research Society of China, 1(1), pp.79-105,2013.10.1007/s40305-013-0010-2Search in Google Scholar
Plan, Y., & Vershynin, R. One - Bit Compressed Sensing by Linear Programming. Communications on Pure and Applied Mathematics, 66(8),pp. 1275-1297,2013.Search in Google Scholar
Patel, V. M., Maleh, R., Gilbert, A. C., & Chellappa, R. Gradient-based image recovery methods from incomplete fourier measurements. Image Processing, IEEE Transactions on, 21(1), 94-105,2013.10.1109/TIP.2011.215980321690011Search in Google Scholar
Do, T. T., Gan, L., Nguyen, N. H., & Tran, T. D. Fast and efficient compressive sensing using structurally random matrices. Signal Processing, IEEE Transactions on, 60(1), pp.139154,2012.Search in Google Scholar
Lechner B, Lieschnegg M, Mariani O, et al. A WAVELET-BASED BRIDGE WEIGH-INMOTION SYSTEM[J]. International Journal on Smart Sensing & Intelligent Systems, 3(4),2010.10.21307/ijssis-2017-409Search in Google Scholar
Needell, D., & Tropp, J. A. CoSaMP: Iterative signal recovery from incomplete and inaccurate samples. Applied and Computational Harmonic Analysis, 26(3),pp. 301-321,2009.10.1016/j.acha.2008.07.002Search in Google Scholar
Zhang, L., Xing, M., Qiu, C. W., Li, J., Sheng, J., Li, Y., & Bao, Z.. Resolution enhancement for inversed synthetic aperture radar imaging under low SNR via improved compressive sensing. Geoscience and Remote Sensing, IEEE Transactions on, 48(10),pp. 38243838,2010.Search in Google Scholar
Yussof H, Wada J, Ohka M. ANALYSIS OF TACTILE SLIPPAGE CONTROL ALGORITHM FOR ROBOTIC HAND PERFORMING GRASP-MOVE-TWIST MOTIONS[J]. International Journal on Smart Sensing & Intelligent Systems, 3(3) ,2010.10.21307/ijssis-2017-397Search in Google Scholar
Wang, J., & Shim, B. On the recovery limit of sparse signals using orthogonal matching pursuit. Signal Processing, IEEE Transactions on, 60(9), pp.4973-4976,2012.Search in Google Scholar
Candes, E. J., Eldar, Y. C., Needell, D., & Randall, P. Compressed sensing with coherent and redundant dictionaries. Applied and Computational Harmonic Analysis, 31(1),pp. 5973,2011.10.1016/j.acha.2010.10.002Search in Google Scholar
Cevher, V., Boufounos, P., Baraniuk, R. G., Gilbert, A. C., & Strauss, M. J. (2009, April). Near-optimal bayesian localization via incoherence and sparsity. In Proceedings of the 2009 International Conference on Information Processing in Sensor Networks (pp. 205-216). IEEE Computer Society.Search in Google Scholar
Padmanabhan,K.; Dhanalakshmi, T.; Image Compression and PSNR Ratio-for an Intensity Image Using Wavelet transform, Journal of the Instrument Society of India,Vol.42 ,2012.Search in Google Scholar
