Rodrigo Capobianco Guido, Tulay Adali, Emil Björnson, Laure Blanc-Féraud, Ulisses Braga-Neto, Behnaz Ghoraani, Christian Jutten, Alle-Jan Van Der Veen, Hong Vicky Zhao, Xiaoxing Zhu
It is our great pleasure to introduce the first part of this special issue to you! The IEEE Signal Processing Society (SPS) has completed 75 years of remarkable service to the signal processing community. When the Society was founded in 1948, we couldn’t imagine, for instance, how wireless networks of smartphones would be able to connect us easily at all times, or that an image processing algorithm would be able to detect cancer in a few seconds. Those are just simple examples of the immense technological progress over the past 75 years, which became possible thanks in great part to the dedicated work of professional members of the SPS.
A special issue of IEEE Signal Processing Magazine was published 25 years ago to celebrate the 50th anniversary of the SPS. To celebrate the 75th anniversary, we have focused on what has happened during the previous 25 years in the field of signal processing, in addition to the main perspectives considering both societal and technical aspects in different domains covered by our Society. In response to an open call for papers, we received 41 white paper submissions. Among those, 18 were selected and invited to be considered for publication upon submission of a full version. Finally, 11 were accepted for inclusion in this first part of the special issue, while the remaining ones will appear in the upcoming second part.
The first three articles in this first part of the special issue focus on the history of the SPS. The article by Petropulu (SPS president) et al. [A1] describes the extraordinary growth we have witnessed in the field of digital signal processing (DSP) since 1998, where the SPS played a fundamental role in promoting cross-disciplinary collaboration and knowledge sharing. Then, the article by Ward (former SPS President) [A2] focuses on women researchers and volunteers and their active role within the SPS. Finally, Pérez-Neira (SPS vice president, conferences) et al. [A3] present an article that comments on the most prominent SPS conferences and their evolution. These articles also discuss the main challenges and opportunities for the SPS.
Next, we have a powerful testimony by Edwards [A4], who has contributed significantly to our magazine and Society over the years. He begins by recalling a very special occasion: the day he was 14 years old and visited the 1969 IEEE International Convention & Exhibition and decided on his future career. Then, using his unique journalistic skills, he narrates lots of interesting events with significant value to our DSP community.
As signal processing can be classified along techniques and methods such as sampling, transforms, statistical techniques including machine learning, and so on, it can also be partitioned into major application areas, such as speech and audio, image processing and multimedia, communication and sensor array processing. Our technical committees (TCs) and unified Editors Information Classification Scheme (EDICS) reflect these dual partitionings. The selected feature articles included in this special issue provide a cross section of those fields. Particularly, in this first issue, we present seven of these feature articles. The first one, authored by Leus et al. [A5] describes the role of graph signal processing for signal analysis over the recent decades in a variety of applications, including image and video processing; social, transportation, communication, and brain networks; recommender systems; financial engineering; distributed control; and learning. The second feature article is by Aviyente et al. [A6]. In it, the authors offer a brief history of the IEEE Bioimaging and Signal Processing TC, providing an overview of the main technological and methodological contributions and highlight promising new directions. Then, Bajic´ et al. [A7] review both the history of multimedia signal processing as well as the IEEE Multimedia Signal Processing TC, with a focus on the last three decades.
The fourth feature article we present in this special issue is authored by Liu et al. [A8], where an overview of the IEEE Sensor Array and Multichannel TC and its activities are introduced, followed by the main technological advances and new developments in the area along with promising future research directions. The fifth feature article, authored by Pesavento et al. [A9], presents an overview and advances in multiple-input, multiple-output systems, including details on direction of arrival, direction of departure, time delay of arrival, and Doppler mechanisms. The sixth feature article is authored by Björnson et al. [A10] and presents the story of wireless communication technologies over the past 25 years, including the advances in air interface, channel coding, source compression, connection protocols, and related areas, covering from 2G to 5G technologies. Finally, the seventh feature article, authored by Elbir et al. [A11], describes relevant details on the development of beamformers, emphasizing minimum-variance distortionless response strategies and the corresponding major breakthroughs over the past decades.
This concludes the first part of this special issue. In the second part, to be published in the magazine’s July issue, another set of relevant articles will appear, concluding our efforts to group together the most significant contributions received to celebrate the 75th anniversary of the SPS. We would like to specially express our gratitude to all our contributing authors and reviewers, in addition to Rebecca Wollman, who efficiently helped us with all the administrative details, and the entire team, led by Sharon Turk, who brilliantly promoted and supervised the editorial process.
We sincerely hope that you enjoy reading the first part of this special issue.
Rodrigo Capobianco Guido is the lead guest editor of this special issue.
Rodrigo Capobianco Guido (firstname.lastname@example.org) received his Ph.D. degree in computational applied physics from the University of São Paulo (USP), Brazil, in 2003. Following two postdoctoral programs in signal processing at USP, he obtained the title of associate professor in signal processing, also from USP, in 2008. Currently, he is an associate professor at São Paulo State University, São José do Rio Preto, São Paulo, 15054-000, Brazil. He has been an area editor of IEEE Signal Processing Magazine and was recently included in Stanford University’s rankings of the world’s top 2% scientists. His research interests include signal and speech processing based on wavelets and machine learning. He is a Senior Member of IEEE.
Tulay Adali (email@example.com) received her Ph.D. degree in electrical engineering from North Carolina State University. She is a distinguished university professor at the University of Maryland, Baltimore County, Baltimore, MD 21250 USA. She is chair of IEEE Brain and past vice president of technical directions for the IEEE Signal Processing Society (SPS). She is a Fulbright Scholar and an SPS Distinguished Lecturer. She received a Humboldt Research Award, an IEEE SPS Best Paper Award, the University System of Maryland Regents’ Award for Research, and a National Science Foundation CAREER Award. Her research interests include statistical signal processing and machine learning and their applications, with an emphasis on applications in medical image analysis and fusion. She is a Fellow of IEEE and a fellow of the American Institute for Medical and Biological Engineering.
Emil Björnson (firstname.lastname@example.org) is a full (tenured) professor of wireless communication at the KTH Royal Institute of Technology, Stockholm, 100 44, Sweden. He received the 2018 and 2022 IEEE Marconi Prize Paper Awards in Wireless Communications, the 2019 EURASIP Early Career Award, the 2019 IEEE Communications Society Fred W. Ellersick Prize, the 2019 IEEE Signal Processing Magazine Best Column Award, the 2020 Pierre-Simon Laplace Early Career Technical Achievement Award, the 2020 Communication Theory Technical Committee Early Achievement Award, the 2021 IEEE Communications Society Radio Communications Committee Early Achievement Award, and the 2023 IEEE Communications Society Outstanding Paper Award. His work has also received six Best Paper Awards at conferences. He is a Fellow of IEEE, and a Digital Futures and Wallenberg Academy fellow.
Laure Blanc-Féraud (email@example.com) received her Ph.D. degree and habilitation to conduct research in inverse problems in image processing from University Côte d’Azur in 1989 and 2000, respectively. She is a researcher with Informatique Signaux et Systèmes at Sophia Antipolis (I3S) Lab, the University Côte d’Azur, Centre national de la recherche scientifique (CNRS), Sophia Antipolis, 06900 France. She served/serves on the IEEE Biomedical Image and Signal Processing Technical Committee (2007–2015; 2019–) and has been general technical chair (2014) and general chair (2021) of the IEEE International Symposium on Biomedical Imaging. She has been an associate editor of SIAM Imaging Science (2013–2018) and is currently an area editor of IEEE Signal Processing Magazine. She headed the French national research group GDR Groupement de recherche–Information, Signal, Image et ViSion (ISIS) of CNRS on Information, Signal Image and Vision (2021–2018). Her research interests include inverse problems in image processing using partial differential equation and optimization. She is a Fellow of IEEE.
Ulisses Braga-Neto (firstname.lastname@example.org) received his Ph.D. degree in electrical and computer engineering from Johns Hopkins University in 2002. He is a professor in the Electrical and Computer Engineering Department, Texas A&M University, College Station TX 77843 USA. He is founding director of the Scientific Machine Learning Lab at the Texas A&M Institute of Data Science. He is an associate editor of IEEE Signal Processing Magazine and a former elected member of the IEEE Signal Processing Society Machine Learning for Signal Processing Technical Committee and the IEEE Biomedical Imaging and Signal Processing Technical Committee. He has published two textbooks and more than 150 peer-reviewed journal articles and conference papers. He received the 2009 National Science Foundation CAREER Award. His research focuses on machine learning and statistical signal processing. He is a Senior Member of IEEE.
Behnaz Ghoraani (email@example.com) received her Ph.D. from the Department of Electrical and Computer Engineering, Ryerson University, Toronto, Canada, followed by a Postdoctoral Fellow period with the Faculty of Medicine, University of Toronto, Toronto, Canada. She is an associate professor of electrical engineering and computer science at Florida Atlantic University, Boca Raton FL 33431 USA, with a specialization in biomedical signal analysis, machine learning, wearable and assistive devices for rehabilitation, and remote home monitoring. She is an associate editor of IEEE Journal of Biomedical and Health Informatics and BioMedical Engineering OnLine Journal. Her research has received recognition through multiple best paper awards and the Gordon K. Moe Young Investigator Award. Her research has been funded by grants from the National Institutes of Health, the National Science Foundation (including a CAREER Award), and the Florida Department of Health. She is an esteemed member of the Board of Scientific Counselors of National Library of Medicine, as well as the IEEE SPS Biomedical Signal and Image Professional Technical Committee. She has also taken on the role of the IEEE Women in Signal Processing Committee Chair and an Area Editor for the IEEE SPM eNewsletter.
Christian Jutten (firstname.lastname@example.org) received his Ph.D. and Doctor es Sciences degrees from Grenoble Polytechnic Institute, France, in 1981 and 1987, respectively. He was an associate professor (1982–1989) and a professor (1989–2019), and has been a professor emeritus since September 2019 at University Grenoble Alpes, Saint-Martin-d’Hères 38400. He was an organizer or program chair of many international conferences, including the first Independent Component Analysis Conference in 1999 (ICA’99) and the 2009 IEEE International Workshop on Machine Learning for Signal Processing. He was the technical program cochair of ICASSP 2020. Since 2021, he has been editor-in-chief of IEEE Signal Processing Magazine. Since the 1980s, his research interests have been in machine learning and source separation, including theory and applications (brain and hyperspectral imaging, chemical sensing, and speech). He is a Fellow of IEEE and a fellow of the European Association for Signal Processing.
Alle-Jan Van Der Veen (email@example.com) received his Ph.D. in system theory at the Circuits and Systems Group, Department of Electrical Engineering, TU Delft, The Netherlands, with a postdoctoral research position at Stanford University, USA. He is a professor and chair of the Signal Processing Systems group at Delft University of Technology, Delft, 2628, The Netherlands. He was editor-in-chief of IEEE Transactions on Signal Processing and IEEE Signal Processing Letters. He was an elected member of the IEEE Signal Processing Society (SPS) Board of Governors. He was chair of the IEEE SPS Fellow Reference Committee, chair of the IEEE SPS Signal Processing for Communications Technical Committee, and technical cochair of ICASSP 2011 (Prague). He is currently the IEEE SPS vice president of technical directions (2022–2024). His research interests are in the areas of array signal processing and signal processing for communication, with applications to radio astronomy and sensor network localization. He is a Fellow of IEEE and a fellow of the European Association for Signal Processing.
Hong Vicky Zhao (firstname.lastname@example.org) received her Ph.D. degree in electrical engineering from the University of Maryland, College Park, in 2004. Since May 2016, she has been an associate professor with the Department of Automation, Tsinghua University, Beijing, 100084, China. She received the IEEE Signal Processing Society 2008 Young Author Best Paper Award. She is the coauthor of “Multimedia Fingerprinting Forensics for Traitor Tracing” (Hindawi, 2005), “Behavior Dynamics in Media-Sharing Social Networks” (Cambridge University Press, 2011), and “Behavior and Evolutionary Dynamics in Crowd Networks” (Springer, 2020). She was a member of the IEEE Signal Processing Society Information Forensics and Security Technical Committee and the Multimedia Signal Processing Technical Committee. She is the senior area editor, area editor, and associate editor of IEEE Signal Processing Letters, IEEE Signal Processing Magazine, IEEE Transactions on Information Forensics and Security, and IEEE Open Journal of Signal Processing. Her research interests include media-sharing social networks, information security and forensics, digital communications, and signal processing.
Xiaoxing Zhu (email@example.com) received her Dr.-Ing. degree and her “Habilitation” in signal processing from the Technical University of Munich (TUM), in 2011 and 2013, respectively. She is the chair professor for data science in Earth observation at TUM, Munich, 80333, Germany. She was founding head of the “EO Data Science” Department at the Remote Sensing Technology Institute, German Aerospace Center. Since October 2020, she has served as a director of the TUM Munich Data Science Institute. She is currently a visiting artificial intelligence professor at the European Space Agency’s Phi Lab. Her research interests include remote sensing and Earth observation, signal processing, machine learning, and data science, with their applications to tackling societal grand challenges, e.g., global urbanization, the United Nations’ sustainable development goals, and climate change. She is a Fellow of IEEE.
[A1] A. Petropulu, J. M. F. Moura, R. K. Ward, and T. Argiropoulos, “Empowering the growth of signal processing,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 14–22, Jul. 2023, doi: 10.1109/MSP.2023.3262905.
[A2] R. K. Ward, “The evolution of women in signal processing and science, technology, engineering, and mathematics,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 23–35, Jul. 2023, doi: 10.1109/MSP.2023.3236475.
[A3] A. I. Perez-Neira, F. Pereira, C. Regazzoni, and C. Johnson, “IEEE signal processing society flagship conferences over the past 10 years,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 36–45, Jul. 2023, doi: 10.1109/MSP.2023.3240852.
[A4] J. Edwards, “How the 1969 IEEE convention and exhibition changed my life forever,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 46–48, Jul. 2023, doi: 10.1109/MSP.2023.3253254.
[A5] G. Leus, A. G. Marques, J. M. F. Moura, A. Ortega, and D. I. Shuman, “Graph signal processing,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 49–60, Jul. 2023, doi: 10.1109/MSP.2023.3262906.
[A6] S. Aviyente et al., “From nano to macro,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 61–71, Jul. 2023, doi: 10.1109/MSP.2023.3242833.
[A7] I. V. Bajic´, M. Mrak, F. Dufaux, E. Magli, and T. Chen, “Multimedia signal processing,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 72–79, Jul. 2023, doi: 10.1109/MSP.2023.3260989.
[A8] W. Liu, M. Haardt, M. S. Greco, C. F. Mecklenbräuker, and P. Willett, “Twenty-five years of sensor array and multichannel signal processing,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 80–91, Jul. 2023, doi: 10.1109/MSP.2023.3258060.
[A9] M. Pesavento, M. Trinh-Hoang, and M. Viberg, “Three more decades in array signal processing research,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 92–106, Jul. 2023, doi: 10.1109/MSP.2023.3255558.
[A10] E. Björnson, Y. C. Eldar, E. G. Larsson, A. Lozano, and H. V. Poor, “Twenty-five years of signal processing advances for multiantenna communications,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 107–117, Jul. 2023, doi: 10.1109/MSP.2023.3261505.
[A11] A. M. Elbir, K. V. Mishra, S. A. Vorobyov, and R. W. Heath Jr., “Twenty-five years of advances in beamforming,” IEEE Signal Process. Mag., vol. 40, no. 4, pp. 118–131, Jul. 2023, doi: 10.1109/MSP.2023.3262366.
Digital Object Identifier 10.1109/MSP.2023.3269591