A Discrete Time and Frequency Wigner Distribution: Properities and Implementation
John M. O’Toole, Mostefa Mesbah, B. Boashash
Abstract
Open-access reader
John M. O’Toole, Mostefa Mesbah, B. Boashash
Abstract
Open-access reader
Time-frequency distributions are used in the analysis and processing of nonstationary signals. The Wigner-Ville distribution (WVD) is a fundamental time-frequency distribution uniquely satisfying many desirable mathematical properties. The realisation of this distribution for hardware or software platforms requires a discrete version. Historically the majority of the work on deriving discrete versions of the WVD has focused on creating alias-free distributions, often resulting in a loss of some desirable properties. Here a new discrete time and frequency WVD will be presented for nonperiodic signals and will be examined both in terms of its properties and aliasing. In particular unitarity, an assumed property for optimum time-frequency detection and signal estimation, and invertibility, a useful property especially for time-frequency filtering, will be examined. An efficient implementation of the distribution using standard real-valued fast Fourier transforms will also be presented.
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Time-frequency distributions are used in the analysis and processing of nonstationary signals. The Wigner-Ville distribution (WVD) is a fundamental time-frequency distribution uniquely satisfying many desirable mathematical properties. The realisation of this distribution for hardware or software platforms requires a discrete version. Historically the majority of the work on deriving discrete versions of the WVD has focused on creating alias-free distributions, often resulting in a loss of some desirable properties. Here a new discrete time and frequency WVD will be presented for nonperiodic signals and will be examined both in terms of its properties and aliasing. In particular unitarity, an assumed property for optimum time-frequency detection and signal estimation, and invertibility, a useful property especially for time-frequency filtering, will be examined. An efficient implementation of the distribution using standard real-valued fast Fourier transforms will also be presented.
Key concepts: Aliasing, Alias, Property (philosophy), Wigner distribution function, Time–frequency analysis, Algorithm, Distribution (mathematics), Discrete Fourier transform (general)