This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Donoho D L, “Compressed sensing”, IEEE Transactions on Information Theory, vol. 52, No. 4, 2006, pp. 1289-1306.10.1109/TIT.2006.871582Search in Google Scholar
Daode Zhang,Yangliu Xue,Xuhui Ye, Yanli Li,”Research On Chips’ Defect Extraction Based On Image-matching “, International Journal on Smart Sensing and Intelligent Systems (S2IS), Mar 10. 2014, pp. 321-336.10.21307/ijssis-2017-658Search in Google Scholar
Tsaig Y, Donoho D L, “Extensions of compressed sensing”, Signal Processing,vol. 86, No. 3,2006, pp. 533-548.10.1016/j.sigpro.2005.05.028Search in Google Scholar
James E. Fowler, Sungkwang Mun, and Eric W. Tramel,”Multi-scale block compressed sensing with smoothed projected landweber reconstruction”, 19th European Signal Processing Conference, Barcelona, Spain,2011.Search in Google Scholar
Feng LUO, Fengjian HU,”A Comprehensive Survey Of Vision Based Vehicle Intelligent Front Light System”,International Journal on Smart Sensing and Intelligent Systems (S2IS), June 1. 2014, pp. 701-723.10.21307/ijssis-2017-677Search in Google Scholar
Pu Jian,Zhang Junping,” Super-Resolution through Dictionary Learning and Sparse Representation”,[J].pattern recognition and artificial intelligence, 2010,pp. 335-340.Search in Google Scholar
Guohui Wu, Xingkun Li, Jiyang Dai.”Improved Measure Algorithm Based On CoSaMP For Image Recovery “,International Journal on Smart Sensing and Intelligent Systems (S2IS), June 1. 2014, pp. 724739.Search in Google Scholar
Candes E, Romberg J,” Sparsity and incoherence in compressive sampling”,[J]. Inverse Problems, vol. 23, No. 3, 2007, pp. 969-985.10.1088/0266-5611/23/3/008Search in Google Scholar
Ahadul Imam, Justin Chi, Mohammad Mozumdar,”Data Compression And Visualization For Wireless Sensor Networks “,International Journal on Smart Sensing and Intelligent Systems (S2IS),Dec 1. 2015, pp. 2083-2115.10.21307/ijssis-2017-844Search in Google Scholar
Payman Moallem1,”Compensation Of Capacitive Differential Pressure Sensor Using Multi Layer Perceptron Neural Network”, International Journal on Smart Sensing and Intelligent Systems (S2IS), Sep
I. 2015, pp. 1443-1463.10.21307/ijssis-2017-814Search in Google Scholar
M. Afonso, J. Bioucas-Dias, M. Figueiredo, “Fast image recovery using variable splitting and constrained optimization”,[J]. IEEE Transactions on Signal Processing, vol. 19, No. 9, 2010, pp. 2345-235.10.1109/TIP.2010.204791020378469Search in Google Scholar
Guo K and Labate D, “Optimally Sparse multidimensional representation using shearlets “,SIAM J. Math. Anal, Vol. 39, 2007, pp. 298-318.10.1137/060649781Search in Google Scholar
Easley G, Labate D, Lim W.”Sparse Directional image representations using the discrete Shearlet transform”, [J].Applied and Computational Harmonic Analysis, vol. 25,2008, pp. 25-46.10.1016/j.acha.2007.09.003Search in Google Scholar
Do T T, Tran T D, Lu G, “Fast compressive sampling with structurally random matrices” Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing. Washington D C: IEEE Computer Society Press, 2008, pp. 3369-3372.10.1109/ICASSP.2008.4518373Search in Google Scholar
Chen SSB, Donoho D L, M A Saunders, “Atomic decomposition by basis pursuit”, [J]. SIAM Journal on Scientific Computation, vol. 20, No. 1, 1998, pp. 33-61.10.1137/S1064827596304010Search in Google Scholar
Tropp J A. Greed is good, ‘‘Algorithmic results for sparse approximation”,[J]. IEEE Transactions on Information Theory, vol. 50, No. 10, 2004, pp. 2231-2242.10.1109/TIT.2004.834793Search in Google Scholar
Blumensath T, Davies M E, ‘Normalised iterative hard thresholding:guaranteed stability and performance”,[J],IEEE Journal of Selected Topics in Signal Processing, vol. 4, No. 2,2010, pp. 298-309.10.1109/JSTSP.2010.2042411Search in Google Scholar
Wenqing Chen, 2 Tao Wang and 3 Bailing Wang, ‘Design Of Digital Image Encryption Algorithm Based On Mixed Chaotic Sequences” International Journal on Smart Sensing and Intelligent Systems (S2IS), Dec. 1. 2014, pp. 1453-1469.10.21307/ijssis-2017-715Search in Google Scholar
Yongqing Wang1* and Xiling Liu, “Face Recognition Based On Improved Support Vector Clustering “,International Journal on Smart Sensing and Intelligent Systems (S2IS), Dec. 1. 2014, pp. 1807-1829.10.21307/ijssis-2017-734Search in Google Scholar
Qu Xiao-Bo, Yan Jing-Wen, Zhu Zi-Qian, Chen Ben-Gang. “Multipulse coupled neural networks”. In Proceedings of International Conference on Bio-Inspired Computing Theories and Applications. Zhengzhou, China: Publishing House of Electronics Industry. 2007,pp.563-565.Search in Google Scholar
Sen P,Darabi S,”Compressive image super-resolution”, Proceedings of Signals, Systems and Computers. Los Alamitos:IEEE Computer Society Press,2009,pp. 1235-1242.10.1109/ACSSC.2009.5469968Search in Google Scholar
Yang C, Wright J, Huang T, Ma Y,”Image super-resolution via sparse representation”,[J].IEEE Trans. Image Process, vol. 19, No. 11, 2010.pp. 2861-2873.10.1109/TIP.2010.205062520483687Search in Google Scholar
J. Bioucas-Dias, M. Figueiredo,”A new TwIST: Two-step iterative shrinkage/thresholding algorithms for image restoration”, [J]. IEEE Transactions on Image Processing, vol. 16, No. 12, 2007, pp. 2992-3004.10.1109/TIP.2007.90931918092598Search in Google Scholar
A. Beck, M. Teboulle,”A fast iterative shrinkage-thresholding algorithm for linear inverse problems”, [J]. SIAM Journal on Imaging Sciences, vol. 2, No. 1, 2009, pp. 183-202.10.1137/080716542Search in Google Scholar