Spline-Like Chebyshev Polynomial Representation for Compressed Sensing (CROSBI ID 681279)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Vlašić, Tin ; Ivanković, Jelena ; Tafro, Azra ; Seršić, Damir
engleski
Spline-Like Chebyshev Polynomial Representation for Compressed Sensing
Compressed sensing is a technique for signal sampling below the Nyquist rate, based on the assumption that the signal is sparse in some transform domain. The acquired signal is represented in a compressed form that is appropriate for storage, transmission and further processing. In this paper, use of the Chebyshev polynomials of the first kind on intervals for an efficient representation of one-dimensional, continuoustime signals is proposed. To avoid boundary artifacts, a desired number of derivatives are equalized on each interval end in a spline-like fashion. Unlike splines, the proposed system of equations is underdetermined to provide a necessary degree of freedom for achieving sparsity using the l1 optimization. The obtained parametric model fits into the compressed sensing setup and offers a new paradigm for efficient processing of analog data on a digital computer. Simulation results of the proposed measurement system and an example of data processing are given to prove its potential.
polynomial approximation ; parametric signal model ; analog-to-information conversion ; splines
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Podaci o prilogu
135-140.
2019.
objavljeno
10.1109/ISPA.2019.8868926
Podaci o matičnoj publikaciji
Proceedings of the 11th International Symposium on Image and Signal Processing and Analysis
Lončarić, Sven ; Bregović, Robert ; Carli, Marco ; Subašić, Marko
Zagreb: Sveučilište u Zagrebu
Podaci o skupu
11th International Symposium on Image and Signal Processing and Analysis (ISPA 2019)
predavanje
23.09.2019-25.09.2019
Dubrovnik, Hrvatska