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Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

Big data can be a blessing: with very large training data sets it becomes possible to perform complex learning tasks with unprecedented accuracy. Yet, this improved performance comes at the price of enormous computational challenges. Thus, one may wonder: Is it possible to leverage the information content of huge data sets while keeping computational resources under control? 

Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

Formulas for estimating and tracking the (time-dependent) frequency, form factor, and amplitude of harmonic time series are presented in this lecture note; in particular, sine-dominant signals, where the harmonics follow roughly the dominant first harmonic, such as photoplethysmography (PPG) and breathing signals. Special attention is paid to the convergence behavior of the algorithm for stationary signals and the dynamic behavior in case of a transition to another stationary state. The latter issue is considered to be important for assessing the tracking abilities for nonstationary signals.

Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

Imagine standing on a street corner in the city. With your eyes closed you can hear and recognize a succession of sounds: cars passing by, people speaking, their footsteps when they walk by, and the continuous falling of rain. The recognition of all these sounds and interpretation of the perceived scene as a city street soundscape comes naturally to humans. It is, however, the result of years of "training": 

Section: Publications & Resources

Greg Mori is Senior Research Director for RBC's Borealis AI and a Professor in the School of Computing Science at Simon Fraser University. Greg Mori was born in Vancouver and grew up in Richmond, BC. He received a Ph.D. degree from UC Berkeley in 2004 and an Hon. B.Sc. from the University of Toronto in 1999.  He was a Visiting Scientist at Google in 2014-2015. 

Section: Publications & Resources

The IEEE Signal Processing Society (SPS) recently approved the creation of the Synthetic Aperture Standards Committee.  This body is the first Standards Committee created under the auspices of the SPS and it is actively recruiting new members for its initial roster. 

Section: Publications & Resources

The ME-UYR initiative has started! We are currently looking for students and mentors who are interested in participating in this mentoring event. Please find more information in the Call for Student participants and the Call for Mentors documents within the announcement.  

Section: Publications & Resources

The ME-UYR initiative has started! We are currently looking for students and mentors who are interested in participating in this mentoring event. Please find more information in the Call for Student participants and the Call for Mentors.  

Section: Publications & Resources

The DSLW team is inviting you to submit regular papers to the 2022 IEEE Data Science & Learning Workshop (DSLW 2022), a workshop organized by the IEEE Signal Processing Society (supported by the SPS Data Science Initiative). The workshop aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science, learning theory and applications.

Section: Publications & Resources

Many problems encountered in sensing and imaging can be formulated as estimating a low-rank object from incomplete, and possibly corrupted, linear measurements; prominent examples include matrix completion and tensor completion. 

Section: Publications & Resources

Did you know the Society offers funding under the Member Driven Initiatives program for events that encourage involvement by SPS membership, including local chapters, universities, industry members as well as individual members? Programs under the Member Driven Initiatives include Seasonal Schools, Forums, Regional Meetings, and Chapter Initiatives.