Digital Signal Processing: A Review Journal

Aims & Scope

Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative.

The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing.

Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal.

The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data • machine learning • internet of things • information security • systems biology and computational biology • financial time series analysis • autonomous vehicles • quantum computing • neuromorphic engineering • human-computer interaction and intelligent user interfaces • environmental signal processing • geophysical signal processing including seismic signal processing • chemioinformatics and bioinformatics • audio, visual and performance arts • disaster management and prevention • renewable energy.

View Aims & Scope

---

Metrics & Ranking

Impact Factor

Year	Value
2025	3
2024	2.90

Journal Rank

Year	Value
2024	8050

Journal Citation Indicator

Year	Value
2024	4297

SJR (SCImago Journal Rank)

Year	Value
2024	0.704

Quartile

Year	Value
2024	Q2

h-index

Year	Value
2024	96

---

---

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

---

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Decision Sciences, Engineering and Mathematics, designed to support cutting-edge academic discovery.

---

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Speaker Verification Using Adapted Gaussian Mixture Models

  Citation: 2997

  Authors: Douglas A., Thomas F., Robert B.

• Methods for interpreting and understanding deep neural networks

  Citation: 1834

  Authors: Grégoire, Wojciech, Klaus-Robert

• A survey of modern deep learning based object detection models

  Citation: 713

  Authors: Syed Sahil Abbas, Mohammad Samar, Asra, Nadia, Mamoona, Brian

• Time–frequency feature representation using energy concentration: An overview of recent advances

  Citation: 611

  Authors: Ervin, Igor, Jin

• Massive MIMO is a reality—What is next?

  Citation: 610

  Authors: Emil, Luca, Henk, Jakob, Thomas L.

• Score Normalization for Text-Independent Speaker Verification Systems

  Citation: 462

  Authors: Roland, Michael, Harvey

• Hybrid intelligent techniques for MRI brain images classification

  Citation: 435

  Authors: El-Sayed Ahmed, Tamer, Abdel-Badeeh M.

• Optimal selection of wavelet basis function applied to ECG signal denoising

  Citation: 421

  Authors: Brij N., Arvind K.

• A basis for efficient representation of the S-transform

  Citation: 368

  Authors: R.G.

• Covariance Matching Estimation Techniques for Array Signal Processing Applications

  Citation: 353

  Authors: B, P, R

---