Publications about 'signal reconstruction;'

Articles in journal or book chapters

1. F. Rosu, A. Anghel, R. Cacoveanu, B. Rommen, and M. Datcu. Multiaperture Focusing for Spaceborne Transmitter/Ground-Based Receiver Bistatic SAR. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13:5823-5832, 2020. Keyword(s): autoregressive processes, covariance matrices, eigenvalues and eigenfunctions, radar receivers, radar resolution, radar transmitters, spaceborne radar, synthetic aperture radar, Romania, Bucharest city, eigenvalues, spatial smoothing, principle component analysis, full rank covariance matrix, bistatic data, integer multiple, Akaike information criterion, multiaperture range image, back-projection focusing, autoregressive model, azimuth samples, slow time resampling, antenna pattern compensation, satellite bursts, range compressed pulses, azimuth apertures, azimuth resolution, spaceborne transmitter-stationary receiver bistatic SAR, azimuth focusing, Azimuth, Receivers, Apertures, Focusing, Synthetic aperture radar, Chirp, Satellites, Autoregressive (AR) model, bistatic synthetic aperture radar (SAR), focusing, order estimation, signal reconstruction. [Abstract] [bibtex-entry]



2. Esteban Aguilera, Matteo Nannini, and Andreas Reigber. Multisignal Compressed Sensing for Polarimetric SAR Tomography. IEEE Geosci. Remote Sens. Lett., 5(9):871-875, September 2012. Keyword(s): SAR Processing, SAR Tomography, Tomography, Compressed sensing, Remote sensing, Sensors, Tomography, Vectors, compressed sensing, compressive sensing, CS, geometry, image reconstruction, image sensors, radar imaging, radar polarimetry, synthetic aperture radar, tomography, 3D imaging, DCS, E-SAR sensor, German Aerospace Center, azimuth-range pixel, data collection processing, distributed compressed sensing, multisignal compressed sensing, parallel track, polarimetric L-band data, polarimetric SAR sensor, polarimetric SAR tomography, polarimetric channel, polarimetric synthetic aperture radar sensor, repeat-pass acquisition geometry, signal reconstruction, temporal baseline, tomographic signal, vertical reflectivity function, Compressed sensing (CS), distributed compressed sensing (DCS), polarimetry, synthetic aperture radar (SAR) tomography, L-band, E-SAR, F-SAR. [Abstract] [bibtex-entry]



3. E.J. Candes and Y. Plan. A Probabilistic and RIPless Theory of Compressed Sensing. IEEE Transactions on Information Theory, 57(11):7235-7254, November 2011. Keyword(s): Fourier coefficients, Gaussian model, RIPless theory, compressed sensing, frequency measurements, probabilistic theory, probability distribution, restricted isometry property, signal random model, sparse signals, Fourier analysis, data compression, random processes, signal reconstruction, statistical distributions;. [Abstract] [bibtex-entry]



4. E.J. Candes, J. Romberg, and T. Tao. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on Information Theory, 52(2):489-509, feb. 2006. Keyword(s): Fourier coefficient, convex optimization, discrete-time signal, image reconstruction, incomplete frequency information, linear programming, minimization problem, nonlinear sampling theorem, piecewise constant object, probability value, robust uncertainty principle, signal reconstruction, sparse random matrix, trigonometric expansion, Fourier analysis, convex programming, image reconstruction, image sampling, indeterminancy, linear programming, minimisation, piecewise constant techniques, probability, signal reconstruction, signal sampling, sparse matrices;. [Abstract] [bibtex-entry]

Conference articles

1. E. Candes, N. Braun, and M. Wakin. SPARSE SIGNAL AND IMAGE RECOVERY FROM COMPRESSIVE SAMPLES. In Biomedical Imaging: From Nano to Macro, 2007. ISBI 2007. 4th IEEE International Symposium on, pages 976-979, april 2007. Keyword(s): compressive sampling, data acquisition, image recovery, magnetic resonance imaging, medical imaging, model-based framework, random measurements, random noise-like basis, signal reconstruction, sparse signal recovery, biomedical MRI, biomedical measurement, data acquisition, image coding, image reconstruction, image sampling, medical image processing, random noise, sparse matrices;. [Abstract] [bibtex-entry]



2. E. Candes and J. Romberg. Robust Signal Recovery from Incomplete Observations. In Proc. IEEE Int. Conf. Image Processing, pages 1281-1284, October 2006. Keyword(s): convex optimization program, linear measurement, sparse signal reconstruction, convex programming, signal reconstruction;. [Abstract] [bibtex-entry]

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This collection of SAR literature is far from being complete.
It is rather a collection of papers which I store in my literature data base. Hence, the list of publications under PUBLICATIONS OF AUTHOR'S NAME should NOT be mistaken for a complete bibliography of that author.

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