Progress in applied Compressive Sampling: A brief review on methods and devices

The CS (Compressive Sampling/Compressed Sensing) is an emerging technique in signal processing, which enables the development of better methods and devices. This talk presents a brief review on the progress of CS after a decade of its developments. First, the principle of the CS and the difference with classical sampling is explained. Then, early developments on CS-methods and related applications are described by giving some well-known examples, such as the single-pixel camera and sparse MRI. A review on the progress of CS research in our group, covering both of theoretical and applied aspects, will also be given.

[1]  R. Gray,et al.  Vector quantization , 1984, IEEE ASSP Magazine.

[2]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[3]  H. Nyquist,et al.  Certain Topics in Telegraph Transmission Theory , 1928, Transactions of the American Institute of Electrical Engineers.

[4]  David L Donoho,et al.  Compressed sensing , 2006, IEEE Transactions on Information Theory.

[5]  D. Donoho,et al.  Sparse MRI: The application of compressed sensing for rapid MR imaging , 2007, Magnetic resonance in medicine.

[6]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.

[7]  Andriyan Bayu Suksmono,et al.  Compressive Stepped-Frequency Continuous-Wave Ground-Penetrating Radar , 2010, IEEE Geoscience and Remote Sensing Letters.

[8]  Andriyan Bayu Suksmono.  The Sample Allocation Problem and Non-Uniform Compressive Sampling , 2014, ArXiv.

[9]  Emmanuel J. Candès,et al.  Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.

[10]  A. B. Suksmono.  Interpolation of PSF based on compressive sampling and its application in weak lensing survey , 2014 .

[11]  A. B. Suksmono.  Improved Compressive Sampling SFCW Radar by Equipartition of Energy Sampling , 2014 .

[12]  Ting Sun,et al.  Single-pixel imaging via compressive sampling , 2008, IEEE Signal Process. Mag..

[13]  Andriyan Bayu Suksmono.  Deconvolution of VLBI images based on compressive sensing , 2009, 2009 International Conference on Electrical Engineering and Informatics.

[14]  H. Gunawan,et al.  Uniform non-exhaustive search on sparse reconstruction for direction of arrival estimation , 2015, 2015 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob).

[15]  Akira Hirose,et al.  Numerical reconstruction of holographic microscopy images based on matching pursuits on a pair of domains , 2010, 2010 IEEE International Conference on Image Processing.

[16]  A compressive-sampling Stepped-Frequency Continuous Wave sodar system , 2016, 2016 10th International Conference on Telecommunication Systems Services and Applications (TSSA).

[17]  Edmund Taylor Whittaker.  XVIII.—On the Functions which are represented by the Expansions of the Interpolation-Theory , 1915 .

[18]  M. Ruffin.  On being digital. , 1995, Physician executive.

[19]  Andriyan Bayu Suksmono,et al.  Reconstruction of fractional Brownian motion signals from its sparse samples based on Compressive Sampling , 2011, Proceedings of the 2011 International Conference on Electrical Engineering and Informatics.

[20]  Andriyan Bayu Suksmono,et al.  Internet Traffic Matrix Estimation Based on Compressive Sampling , 2017 .