2 research outputs found
Recommended from our members
High-resolution signal synthesis for time-frequency distributions
Bilinear time-frequency distributions (TFDs) offer improved resolution over linear nine-frequency representations (TFRs), but many TFDs are costly to evaluate and are not associated with signal synthesis algorithms. Recently, the spectrogram (SP) decomposition and weighted reversal correlator decomposition have been used to define low-cost, high-resolution TFDs. In this paper, we show that the vector-valued square-root'' of a TFD (VVTFR) provides a representational underpinning for the TFD. By synthesizing signals from modified VVTFRs, we define high-resolution signal synthesis algorithms associated with TFDs. The signal analysis and synthesis packages can be implemented as weighted sums of SP/short-time Fourier Transform signal analysis and synthesis packages, which are widely available, allowing the interested non-specialist easy access to high-resolution methods
Recommended from our members
High-resolution signal synthesis for time-frequency distributions
Bilinear time-frequency distributions (TFDs) offer improved resolution over linear nine-frequency representations (TFRs), but many TFDs are costly to evaluate and are not associated with signal synthesis algorithms. Recently, the spectrogram (SP) decomposition and weighted reversal correlator decomposition have been used to define low-cost, high-resolution TFDs. In this paper, we show that the vector-valued ``square-root`` of a TFD (VVTFR) provides a representational underpinning for the TFD. By synthesizing signals from modified VVTFRs, we define high-resolution signal synthesis algorithms associated with TFDs. The signal analysis and synthesis packages can be implemented as weighted sums of SP/short-time Fourier Transform signal analysis and synthesis packages, which are widely available, allowing the interested non-specialist easy access to high-resolution methods