Nonparametric spectral analysis of gapped data via an adaptive filtering approach |
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Authors: | Petre Stoica Guoqing Liu Jian Li Erik G. Larsson |
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Affiliation: | (1) Department of Systems and Control, Uppsala University, PO Box 27, SE-751 03 Uppsala, Sweden;(2) Department of Electrical and Computer Engineering, University of Florida, PO Box 116130, 32611 Gainesville, Florida, USA |
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Abstract: | We present an algorithm for nonparametric complex spectral analysis of gapped data via an adaptive finite impulse response (FIR) filtering approach, referred to as the gapped-data amplitude and phase estimation (GAPES) algorithm. The incomplete data sequence may contain gaps of various sizes. The GAPES algorithm iterates the following two steps: (1) estimating the adaptive FIR filter and the corresponding complex spectrum via amplitude and phase estimation (APES), a nonparametric adaptive FIR filtering approach, and (2) filling in the gaps via a least-squares APES fitting criterion. The initial condition for the iteration is obtained from the available data segments via APES. Numerical results are presented to demonstrate the effectiveness of the proposed GAPES algorithm.This work was supported in part by the Senior Individual Grant Program of the Swedish Foundation for Strategic Research, AFRL/SNAT, Air Force Research Laboratory, Air Force Material Command, USAF, under grant number F33615-99-1-1507, and the National Science Foundation Grant MIP-9457388. The US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notice thereon. |
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Keywords: | Missing data gapped data nonparametric spectral estimation adaptive filtering |
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