Fading Memory and the Convolution Theorem

Several topological and analytical notions of continuity and fading memory for causal and time-invariant filters are introduced, and the relations between them are analyzed. A significant generalization of the convolution theorem that establishes the equivalence between the fading memory property and the availability of convolution representations of linear filters is proved. This result extends a previous similar characterization to a complete array of weighted norms in the definition of the fading memory property. Additionally, the main theorem shows that the availability of convolution representations can be characterized, at least when the codomain is finite-dimensional, not only by the fading memory property but also by the reunion of two purely topological notions that are called minimal continuity and minimal fading memory property. Finally, when the input space and the codomain of a linear functional are Hilbert spaces, it is shown that minimal continuity and the minimal fading memory property guarantee the existence of interesting embeddings of the associated reproducing kernel Hilbert spaces.

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Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-05-27
DOI
https://doi.org/10.1109/tac.2025.3574377
Primary Topic
Computability, Logic, AI Algorithms
Type
article
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article

Fading Memory and the Convolution Theorem

Florian Rossmannek, Juan‐Pablo Ortega
IEEE Transactions on Automatic Control
Computability, Logic, AI Algorithms
article

Fading Memory and the Convolution Theorem

Florian Rossmannek, Juan‐Pablo Ortega
article en

Abstract

Several topological and analytical notions of continuity and fading memory for causal and time-invariant filters are introduced, and the relations between them are analyzed. A significant generalization of the convolution theorem that establishes the equivalence between the fading memory property and the availability of convolution representations of linear filters is proved. This result extends a previous similar characterization to a complete array of weighted norms in the definition of the fading memory property. Additionally, the main theorem shows that the availability of convolution representations can be characterized, at least when the codomain is finite-dimensional, not only by the fading memory property but also by the reunion of two purely topological notions that are called minimal continuity and minimal fading memory property. Finally, when the input space and the codomain of a linear functional are Hilbert spaces, it is shown that minimal continuity and the minimal fading memory property guarantee the existence of interesting embeddings of the associated reproducing kernel Hilbert spaces.

IEEE Transactions on Automatic ControlVol. 70(12)
Nanyang Technological University (SG)
Reduced inequalities
Openalex Percentile: Top 87%
Computability, Logic, AI Algorithms
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