IEEE Journal on Selected Areas in Information Theory
Published by IEEE
eISSN : 2641-8770
Abbreviation : IEEE J. Sel. Area Inf. Theory
Aims & Scope
The IEEE Journal on Special Areas in Information Theory (JSAIT) is a multi-disciplinary journal of special issues focusing on the intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics.
Any field that utilizes the fundamentals of information theory, including concepts such as entropy, compression, coding, mutual information, divergence, capacity, and rate distortion theory is a candidate for a JSAIT special issue.
There will also be special issues for topics firmly within information theory, particularly emerging areas.
View Aims & ScopeMetrics & Ranking
Journal Rank
| Year | Value |
|---|---|
| 2024 | 3097 |
SJR (SCImago Journal Rank)
| Year | Value |
|---|---|
| 2024 | 1.297 |
Journal Citation Indicator
| Year | Value |
|---|---|
| 2024 | 853 |
Quartile
| Year | Value |
|---|---|
| 2024 | Q1 |
h-index
| Year | Value |
|---|---|
| 2024 | 28 |
Abstracting & Indexing
Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.
Subjects & Keywords
Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Engineering and Mathematics, designed to support cutting-edge academic discovery.