Continuous Algebraic Diversity: Unifying Spectral, Wavelet, and Time-Frequency Analysis via Lie Group Actions
Mitchell A. Thornton

TL;DR
This paper introduces a unified algebraic framework for spectral, wavelet, and time-frequency analysis using Lie group actions, providing a criterion for optimal analysis method selection.
Contribution
It extends the algebraic diversity framework to Lie groups, establishing a unified theory and selection criterion for various signal analysis techniques.
Findings
Generalizes analysis selection via a group-averaged estimator
Explains frequency-dependent noise in wavelet analysis through non-unimodularity
Provides a polynomial-time solution for blind group matching
Abstract
We provide a computable criterion for selecting among Fourier, wavelet, and time-frequency analysis by extending the algebraic diversity (AD) framework to Lie groups acting on . To our knowledge, there is no other criterion that provides this selection capability. The group-averaged estimator generalizes from a finite sum over group elements to an integral with respect to Haar measure. A Continuous Replacement Theorem establishes signal-noise separation under equivariance and ergodicity conditions, with a noise operator determined by the Duflo-Moore operator that explains the frequency-dependent noise floor in wavelet analysis as a consequence of the affine group's non-unimodularity. A Unification Theorem shows that classical spectral analysis corresponds to the translation group, wavelet analysis to the affine group, time-frequency…
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