IEEE Journal of Selected Topics in Signal Processing

IEEE Journal of Selected Topics in Signal Processing
Title	IEEE Journal of Selected Topics in Signal Processing
Discipline	Signal processing
Abbreviation	IEEE J. Sel. Top. Signal Process.
Publisher	IEEE
Frequency	Quarterly
History	2007–present
Issn	1932-4553

Contents

IEEE Journal of Selected Topics in Signal Processing is a peer-reviewed periodical covering focused advances in signal processing, distributed by the Institute of Electrical and Electronics Engineers and associated with communities active in IEEE Signal Processing Society, IEEE Communications Society, and related professional bodies. The journal publishes special-topic issues that bridge research from laboratories and conferences such as International Conference on Acoustics, Speech, and Signal Processing, NeurIPS, and ICASSP 2010-era symposia, attracting submissions from authors affiliated with institutions like Massachusetts Institute of Technology, Stanford University, University of Cambridge, Tsinghua University, and ETH Zurich.

History

The journal was established in 2007 to complement flagship titles such as IEEE Transactions on Signal Processing and to provide targeted venues similar to editorial models used by Nature Communications, IEEE Transactions on Information Theory, and themed series like ACM Computing Surveys special collections. Founding editors and guest editors included researchers associated with University of California, Berkeley, Princeton University, University of Illinois Urbana–Champaign, Georgia Institute of Technology, and collaborators who had served on programs for conferences such as ICASSP, IEEE Global Communications Conference, and European Signal Processing Conference. Over time the journal has mirrored shifts in research highlighted at events including CVPR, ICML, and workshops sponsored by NSF and DARPA.

The journal emphasizes concentrated topics within signal processing, often overlapping with themes explored at IEEE International Workshop on Machine Learning for Signal Processing, SIAM Conference on Imaging Science, and panels at ACM Multimedia. Typical topics include adaptive filtering and wavelets linked to work from Bell Labs Research, compressed sensing that references breakthroughs by groups at Rice University and Stanford University, audio and speech processing related to efforts at MIT Media Lab, biomedical signal processing associated with Johns Hopkins University and Harvard Medical School, and array processing with ties to research from University of Michigan and Duke University. Cross-disciplinary issues import methods from Neural Information Processing Systems, International Conference on Learning Representations, and computational imaging communities connected to Caltech and Max Planck Institute investigators.

The journal issues themed collections overseen by guest editors drawn from organizations including Microsoft Research, Google Research, Facebook AI Research, and national labs such as Lawrence Berkeley National Laboratory and Los Alamos National Laboratory. Editorial policies align with standards followed by IEEE Transactions on Signal Processing and editorial boards including members from University of Oxford, Imperial College London, and Kyoto University. It maintains peer review practices comparable to those at Proceedings of the IEEE and coordinates special issues with conferences like ICASSP and workshops under the aegis of IEEE Signal Processing Society committees.

The journal is indexed in bibliographic services and databases used by scholars associated with Clarivate Analytics, Scopus (Elsevier), and university libraries at institutions such as Columbia University, University of Toronto, and Australian National University. Citations and metrics are tracked alongside publications in IEEE Xplore, compared to citation patterns seen in ACM Digital Library entries and aggregated in tools used at Google Scholar, Web of Science, and institutional repositories at CNRS and Max Planck Society.

Scholars from research centers like Harvard University, Yale University, University of California, Los Angeles, Carnegie Mellon University, and National University of Singapore cite the journal's special issues in studies on compressive imaging, sparse representations, and machine-learning-driven signal analysis. The journal's influence is noted at plenaries and tutorials of ICASSP, workshops at ECCV, and panels at SIGGRAPH where cross-cutting signal topics intersect with vision and graphics research. Its articles are often juxtaposed with content from IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, and review venues such as Annual Review of Control, Robotics, and Autonomous Systems.

Noteworthy special issues have aligned with themes prominent at major meetings: a special issue on compressive sensing reflecting research presented at ICASSP 2008 and seminars at Courant Institute, an issue on biomedical signal analysis timed with symposia at IEEE EMBS and ISBI, a collection on machine learning for signal processing corresponding to sessions at NeurIPS and ICLR, and an issue on array processing connected to panels at European Signal Processing Conference and IEEE Sensor Array and Multichannel Signal Processing Workshop. Guest editors have included investigators from Broad Institute, Scripps Research, Rensselaer Polytechnic Institute, and Tata Consultancy Services research labs who coordinated submissions tied to conference programs at IEEE BigData and workshops sponsored by the National Institutes of Health.