TL;DR
The paper introduces the demodulated band transform (DBT), a computationally efficient spectral estimation method that minimizes spectral leakage and is effective for analyzing stationary and non-stationary signals.
Contribution
It presents the DBT as a novel, efficient complex demodulation technique with advantages over existing windowed Fourier decompositions in spectral analysis.
Findings
DBT offers minimal spectral leakage and high computational efficiency.
DBT performs well in adaptive filtering of non-stationary narrowband noise.
Compared to other WFDs, DBT shows favorable results in spectral estimation.
Abstract
Background: Windowed Fourier decompositions (WFD) are widely used in measuring stationary and non-stationary spectral phenomena and in describing pairwise relationships among multiple signals. Although a variety of WFDs see frequent application in electrophysiological research, including the short-time Fourier transform, continuous wavelets, band-pass filtering and multitaper-based approaches, each carries certain drawbacks related to computational efficiency and spectral leakage. This work surveys the advantages of a WFD not previously applied in electrophysiological settings. New Methods: A computationally efficient form of complex demodulation, the demodulated band transform (DBT), is described. Results: DBT is shown to provide an efficient approach to spectral estimation with minimal susceptibility to spectral leakage. In addition, it lends itself well to adaptive filtering of…
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