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


We welcome also submissions in the fundamental areas such as information theory and on mathematical topics with potential applications in signal processing such as functional analysis, stochastic calculus, game theory and group theory. Papers in the classical application areas of signal processing such as telecommunications, speech, image and video processing are welcome only if they contain novel research into methodology. Purely application oriented articles in these areas should be submitted to the relevant dedicated journals.

Digital Signal Processing: A Review Journal also aims to publish quality review articles in addition to occasional focus issues with special emphasis on emerging topics. Discussion articles in which several leading researchers discuss the future of a specific research area are also welcome.

For details of the journal's speeds and other metrics, please visit our Journal Insights pages.

Reproducibility Badge Initiative and Software Publication

The Reproducibility Badge Initiative (RBI) is a collaboration with Code Ocean (CO), a cloud-based computational reproducibility platform that helps the community by enabling sharing of code and data as a resource for non-commercial use. CO verifies the submitted code (and data) and certifies its reproducibility. Code submission will be verified by the Code Ocean team for computational reproducibility by making sure it runs, delivers results and it is self-contained. For more information please visit this help article. Note that an accepted paper will be published independently of the CO application outcome. However, if the paper receives the Reproducibility Badge, it will be given additional exposure by having an attached R Badge, and by being citable at the CO website with a DOI.

We invite Digital Signal Processing authors to convert their open source software into an additional journal publication in Software Impacts, a multi-disciplinary open access journal. Software Impacts provides a scholarly reference to software that has been used to address a research challenge. The journal disseminates impactful and re-usable scientific software through Original Software Publications which describe the application of the software to research and the published outputs.

For more information contact us at: software.impacts@elsevier.com