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10 years of news and resources for members of the IEEE Signal Processing Society

Publications News

In 1882, a banker in Sacramento, Calif., named Frank Miller developed an absolutely unbreakable encryption method. Nearly 140 years later, cryptographers have yet to come up with something better.

Individual feature articles and special issues are two major mechanisms of full-length tutorial surveys of IEEE Signal Processing Magazine (SPM). Since the May 2016 feature article cluster by Jane Wang et al. on brain signal analytics, SPM’s current and past editors-in-chief and their teams have been exploring a different way to complement this existing structure—a feature article cluster (or mini special issue) that allows for a set of three to five solicited articles on a current topic, instead of just one (feature article) or ten to 11 (a special issue).

The advent of new wireless technologies in recent years has created a tremendous increase in the demand for wireless connectivity. The estimated number of mobile device connections exceeds eight billion globally, more than the population of the world, and the growth trend is rapidly increasing as the developing world penetration rate is still in its infancy.

By bringing research into the curriculum, this article explores new opportunities to refresh some classic signal processing courses. Since 2015, we in the Electrical and Electronic Engineering (EEE) Department of Imperial College London, United Kingdom, have explored the extent to which the level of student engagement and learning can be enhanced by inviting the students to perform signal processing exercises on their own physiological data.

Speech coding is a field in which compression paradigms have not changed in the last 30 years. Speech signals are most commonly encoded with compression methods that have roots in linear predictive theory dating back to the early 1940s. 

If John von Neumann were designing a computer today, there’s no way he would build a thick wall between processing and memory. At least, that’s what computer engineer Naresh Shanbhag of the University of Illinois at Urbana-Champaign believes. 

For centuries, humans have been exploring the subsurface structure of planet Earth. Several Earth geophysical applications, such as mining, earthquake studies, and oil and gas exploration, have driven research that produced, over the years, ground-breaking theories and innovative technologies that image Earth’s subsurface. 

In the coming years, cities are expected to deal with an increasing number and type of services for their citizens, all having to do with overarching goals such as sustainability, environment, quality of life, energy saving, just to name a few. As the population living in urban areas is expected to double by 2050, there is a general consensus that any new process will require more than just an incremental upgrading of the cities’ organization, infrastructure, and services provided to its citizens.

Signal processing is always at the heart of the technology that differentiates today’s generations from those of the past is reaffirmed once again by the special issue on Machine Learning for Cognition in Radio Communications and Radar in IEEE Journal of Selected Topics in Signal Processing, February 2018.

The November 2017 special issue of SPM on deep learning for visual understanding surveyed deep-learning solutions under reinforcement; weakly supervised and multimodal settings, investigated their robustness; and presented overviews of their applications in domain adaptation, hashing, semantic segmentation, metric learning, inverse problems in imaging, image-to-text generation, and picture-quality assessment.

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