DocumentCode
730559
Title
Adaptive signal and system approximation and strong divergence
Author
Boche, Holger ; Monich, Ullrich J.
Author_Institution
Lehrstuhl fur Theor. Informationstechnik, Tech. Univ. Munchen, München, Germany
fYear
2015
fDate
19-24 April 2015
Firstpage
3616
Lastpage
3620
Abstract
Many divergence results for sampling series are in terms of the limit superior and not the limit. This leaves the possibility of a convergent subsequence. If there exists a convergent subsequence, adaptive signal processing techniques can be used. In this paper we study sampling-based signal reconstruction and system approximation processes for the space PWπ1 of bandlimited signals with absolutely integrable Fourier transform. For all analyzed examples, which include the peak value of the Shannon and the conjugated Shannon sampling series, we prove strong divergence, i.e., divergence for all subsequences. Hence, adaptive signal processing techniques do not help in these cases. We further analyze whether an adaptive choice of the reconstruction functions in the oversampling case can improve the behavior.
Keywords
Fourier transforms; adaptive signal processing; approximation theory; convergence; signal reconstruction; signal sampling; Shannon sampling series; adaptive signal processing techniques; convergent subsequence; integrable Fourier transform; reconstruction functions; sampling-based signal reconstruction; system approximation processes; Adaptive signal processing; Approximation methods; Convergence; Kernel; Linear systems; Signal reconstruction; Tin; Hilbert transform; Paley-Wiener space; linear time-invariant system; reconstruction; strong divergence;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location
South Brisbane, QLD
Type
conf
DOI
10.1109/ICASSP.2015.7178645
Filename
7178645
Link To Document