Overview
Sampling Theory, Signal Processing, and Data Analysis is a journal focusing on the mathematical aspects of sampling theory, signal processing, and data analysis.
- Welcomes papers on the mathematics of data science and machine learning.
- Encourages cross-disciplinary advances and interactions.
- Publishes high-quality research papers, survey articles, and seminal theoretical papers.
- Covers a wide range of topics from traditional Fourier analytic methods to cutting-edge techniques like Compressive Sensing, Atomic Decomposition, and Deep Learning.
- The journal is a continuation of Sampling Theory in Signal and Image Processing.
This is a transformative journal, you may have access to funding.
- Editors-in-Chief
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- Akram Aldroubi,
- Zuhair Nashed,
- Götz Pfander
- Submission to first decision (median)
- 29 days
- Downloads
- 36,279 (2023)
Latest articles
Journal updates
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Journal Related Books
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Journal information
- Electronic ISSN
- 2730-5724
- Print ISSN
- 2730-5716
- Abstracted and indexed in
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- Astrophysics Data System (ADS)
- Baidu
- CLOCKSS
- CNKI
- CNPIEC
- Dimensions
- EBSCO
- Google Scholar
- Mathematical Reviews
- Naver
- OCLC WorldCat Discovery Service
- Portico
- ProQuest
- SCImago
- SCOPUS
- TD Net Discovery Service
- Wanfang
- zbMATH
- Copyright information