2012European Signal Processing ConferenceRequires access

Signal sampling according to time-varying bandwidth

Rolands Shavelis, Modris Greitāns

Open publisher page 4 citations

Abstract

The paper addresses the problem of signal-dependent sampling of analogue signals according to local bandwidth. An extended sampling theorem is given which states that signals can be sampled non-uniformly and then perfectly reconstructed if spectrum obtained by an extended Fourier transform (EFT) is bandlimited. Since, according to the theorem, the sampling instants are determined by the function used in EFT, the aim is to find such function which reflects the time-varying spectral content of the signal. This, in comparison to uniform sampling, allows reducing the number of samples required to represent the signal. The results have been demonstrated by numerical simulations on two signals.

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What this paper is about

The paper addresses the problem of signal-dependent sampling of analogue signals according to local bandwidth. An extended sampling theorem is given which states that signals can be sampled non-uniformly and then perfectly reconstructed if spectrum obtained by an extended Fourier transform (EFT) is bandlimited. Since, according to the theorem, the sampling instants are determined by the function used in EFT, the aim is to find such function which reflects the time-varying spectral content of the signal. This, in comparison to uniform sampling, allows reducing the number of samples required to represent the signal. The results have been demonstrated by numerical simulations on two signals.

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Available abstract

The paper addresses the problem of signal-dependent sampling of analogue signals according to local bandwidth. An extended sampling theorem is given which states that signals can be sampled non-uniformly and then perfectly reconstructed if spectrum obtained by an extended Fourier transform (EFT) is bandlimited. Since, according to the theorem, the sampling instants are determined by the function used in EFT, the aim is to find such function which reflects the time-varying spectral content of the signal. This, in comparison to uniform sampling, allows reducing the number of samples required to represent the signal. The results have been demonstrated by numerical simulations on two signals.

Key concepts: Bandlimiting, Nonuniform sampling, Coherent sampling, Bandwidth (computing), Sampling (signal processing), Nyquist–Shannon sampling theorem, Fourier transform, SIGNAL (programming language)

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