Approximation by Woven Frames

This paper focuses on the approximation by woven frames in separable Hilbert spaces. We present an iterative method to approximate a signal $f$ based on a given weaving frame, by defining a recursive sequence that converges to the signal $f$. We show that this method converges to a signal that minimizes a specific functional involving the frame coefficients of the given weaving frame. The importance of this method is better understood when the weaving frame used has a large condition number, and the classical frame algorithm is unusable. It is necessary to point out that all numerical experiments in this paper were performed on a 64-bit 2.4 GHz Core i5 processor and 4.00 GB RAM using MATLAB version R2010a.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-10-01
DOI
https://doi.org/10.22130/scma.2025.2056750.2127
Primary Topic
Mathematical Analysis and Transform Methods
Type
article
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article

Approximation by Woven Frames

Hassan Jamali, Reza Pourkani
SHILAP Revista de lepidopterología
Mathematical Analysis and Transform Methods
article

Approximation by Woven Frames

Hassan Jamali, Reza Pourkani
article en

Abstract

This paper focuses on the approximation by woven frames in separable Hilbert spaces. We present an iterative method to approximate a signal $f$ based on a given weaving frame, by defining a recursive sequence that converges to the signal $f$. We show that this method converges to a signal that minimizes a specific functional involving the frame coefficients of the given weaving frame. The importance of this method is better understood when the weaving frame used has a large condition number, and the classical frame algorithm is unusable. It is necessary to point out that all numerical experiments in this paper were performed on a 64-bit 2.4 GHz Core i5 processor and 4.00 GB RAM using MATLAB version R2010a.

SHILAP Revista de lepidopterología
Vali Asr University of Rafsanjan (IR)
Openalex Percentile: Top 16%
Mathematical Analysis and Transform Methods
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