The faces of Convolution: from the Fourier theory to algebraic signal processing
Feng Ji, Wee Peng Tay, Antonio Ortega

TL;DR
This paper provides an overview of convolution across Fourier and algebraic signal processing theories, discussing their relationships and exploring the possibility of a unified approach.
Contribution
It offers a comprehensive comparison of convolution in classical Fourier and algebraic signal processing theories, proposing insights on unification.
Findings
Convolution concepts vary across theories but share underlying principles.
Potential for a unified convolution framework is discussed.
The article clarifies differences and similarities among convolution approaches.
Abstract
In this expository article, we provide a self-contained overview of the notion of convolution embedded in different theories: from the classical Fourier theory to the theory of algebraic signal processing. We discuss their relations and differences. Toward the end, we provide an opinion on whether there is a consistent approach to convolution that unifies seemingly different approaches by different theories.
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Taxonomy
TopicsNeural Networks and Applications
MethodsConvolution
