The Stationary Phase Approximation, Time-Frequency Decomposition and Auditory Processing
Bernard Mulgrew

TL;DR
This paper re-examines the stationary phase principle within time-frequency analysis, introducing a new test for phase rate dominance, leading to a sparse representation method that improves auditory signal processing and modeling.
Contribution
It introduces a novel time-frequency stationary phase approximation with a test for phase rate dominance, enhancing analysis and synthesis of auditory signals.
Findings
Identifies stationary phase regions in elementary signals.
Proposes a sparsity-based approach for TF analysis and synthesis.
Predicts and quantifies auditory masking effects.
Abstract
The principle of stationary phase (PSP) is re-examined in the context of linear time-frequency (TF) decomposition using Gaussian, gammatone and gammachirp filters at uniform, logarithmic and cochlear spacings in frequency. This necessitates consideration of the use the PSP on non-asymptotic integrals and leads to the introduction of a test for phase rate dominance. Regions of the TF plane that pass the test and don't contain stationary phase points contribute little or nothing to the final output. Analysis values that lie in these regions can thus be set to zero, i.e. sparsity. In regions of the TF plane that fail the test or are in the vicinity of stationary phase points, synthesis is performed in the usual way. A new interpretation of the location parameters associated with the synthesis filters leads to: (i) a new method for locating stationary phase points in the TF plane; (ii) a…
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