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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Glentis, G. O. Jakobsson, A. Angelopoulos, K. Univ Peloponnese Dept Informat & Telecommun Sparti Greece Lund Univ Dept Math Stat Lund Sweden

ISBN: (纸本)9781479928934

In this work, we examine a computationally efficient block-updating scheme for estimating the spectral content of signals with missing samples. The work is an extension of our recent single-sample data interpolation updating of the Iterative Adaptive Approach (IAA), being reformulated to incorporate blocks of samples. The proposed implementation offers a substantial complexity reduction as compared to earlier presented updating schemes, without sacrificing the quality of the resulting spectral estimates more than marginally (if at all).

关键词： spectrum estimation theory and methods Iterative Adaptive Approach (IAA) fast algorithms

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TIME-UPDATING IAA-BASED SPECTRAL ESTIMATES WITH MISSING SAMPLES USING DATA INTERPOLATION

TIME-UPDATING IAA-BASED SPECTRAL ESTIMATES WITH MISSING SAMP...

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Glentis, G. O. Jakobsson, A. Angelopoulos, K. Univ Peloponnese Dept Sci & Technol Telecommun Sparti Greece Lund Univ Dept Mah Stat S-22100 Lund Sweden

ISBN: (纸本)9781479903566

In this work, we propose a computationally efficient time-updating algorithm for estimating the spectral content of a signal with missing samples. The algorithm extends earlier work on the topic by formulating a data-interpolation scheme reducing the required complexity to a fraction of the earlier efficient implementation, without resulting in any noticeable loss of performance for even a quite large degree of missing samples.

关键词： spectrum estimation theory and methods Iterative Adaptive Approach (IAA) fast algorithms

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TIME-UPDATING IAA-BASED SPECTRAL ESTIMATES WITH MISSING SAMPLES USING DATA INTERPOLATION

TIME-UPDATING IAA-BASED SPECTRAL ESTIMATES WITH MISSING SAMP...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： G. O. Glentis A. Jakobsson K. Angelopoulos Dept. of Science and Technology of Telecommunications University of Peloponnese Greece Dept. of Mathematical Statistics Lund University Sweden

ISBN: (纸本)9781479903573

关键词： spectrum estimation theory and methods Iterative Adaptive Approach (IAA) fast algorithms Interpolation Aurora A Signaling Pathway overrun a signal clear (a signal)

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Efficient Implementation of Iterative Adaptive Approach Spectral estimation Techniques

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2011年第9期59卷 4154-4167页

作者： Glentis, George-Othon Jakobsson, Andreas Univ Peloponnese Dept Sci & Technol Telecommun Tripolis 22100 Greece Lund Univ Dept Math Stat SE-22100 Lund Sweden

This paper presents computationally efficient implementations for several recent algorithms based on the iterative adaptive approach (IAA) for uniformly sampled one-and two-dimensional data sets, considering both the complete data case, and the cases when the data sets are missing samples, either lacking arbitrary locations, or having gaps or periodically reoccurring gaps. By exploiting the method's inherent low displacement rank, together with the development of suitable Gohberg-Semencul representations, and the use of data dependent trigonometric polynomials, the proposed implementations are shown to offer a reduction of the necessary computational complexity by at least one order of magnitude. Numerical simulations together with theoretical complexity measures illustrate the achieved performance gain.

关键词： iterative adaptive approach (IAA) fast algorithms spectrum estimation theory and methods

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