A Fast Algorithm for Selective Signal Extrapolation with Arbitrary Basis Functions. (27th January 2011)

• Record Type: Journal Article
• Authors: Seiler Seiler, Jürgen Jürgen; Kaup Kaup, André André
• Other Names: Pérez-Neira Pérez-Neira Ana Ana Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2011(2011)
• Publication Date: 2011-01-27
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2011/495394
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : Signal extrapolation is an important task in digital signal processing for extending known signals into unknown areas. The Selective Extrapolation is a very effective algorithm to achieve this. Thereby, the extrapolation is obtained by generating a model of the signal to be extrapolated as weighted superposition of basis functions. Unfortunately, this algorithm is computationally very expensive and, up to now, efficient implementations exist only for basis function sets that emanate from discrete transforms. Within the scope of this contribution, a novel efficient solution for Selective Extrapolation is presented for utilization with arbitrary basis functions. The proposed algorithm mathematically behaves identically to the original Selective Extrapolation but is several decades faster. Furthermore, it is able to outperform existent fast transform domain algorithms which are limited to basis function sets that belong to the corresponding transform. With that, the novel algorithm allows for an efficient use of arbitrary basis functions, even if they are only numerically defined.