Constructive Sampling Frameworks in Signal Processing and Modern Data Analysis
This special issue belongs to the section "Computational and Numerical Mathematics".
Special Issue Information
Dear Colleagues,
This Special Issue collects rigorous theoretical advances and computationally oriented contributions at the interface of sampling theory, constructive approximation, and data-driven signal processing. We invite original research and authoritative surveys that develop sampling and reconstruction frameworks (classical and generalized), operator-based approximation techniques, stability and error analyses, and computational schemes for modern signal/image processing and data analysis. Contributions that connect rigorous approximation results with practical implementation, numerical experiments, or data-centered validation—including applications in compressed sensing, graph signals, fractional models, and machine-learning-informed sampling—are especially welcome. The Special Issue is associated with the 4th International Conference: Constructive Mathematical Analysis (ICCMA 2026, 01-02 July, Online), providing a strong pool of extended contributions; all submissions will undergo MDPI’s standard peer review.
Prof. Dr. Tuncer Acar
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
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Keywords
- sampling theory
- constructive approximation
- signal processing
- data analysis
- reconstruction methods
- computational methods
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Published Papers
AppliedMath - ISSN 2673-9909