IEEE Signal Processing Magazine

I am writing this column on the first official day of spring while “sheltering in place” in Northern California. In these uncertain times, we are all experiencing the anxiety that comes from an unpredictable situation that we do not control; the shock of seeing, perhaps for the first time, all of the shelves in grocery stores empty; and the stress of working, living, and sleeping in the same place.

Since the 1970s, various image and video coding techniques have been explored, and some of them have been included in the video coding standards issued by the International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC) Motion Pictures Expert Group (MPEG) and International Telecommunication Union-Telecommunication Standardization Sector (ITU-T) Video Coding Experts Group (VCEG).

The current big data era routinely requires the processing of large-scale data on massive distributed computing clusters. In these applications, data sets are often so large that they cannot be housed in the memory and/or the disk of any one computer. Thus, the data and the processing are typically distributed across multiple nodes.

Batch training of machine learning models based on neural networks is well established, whereas, to date, streaming methods are largely based on linear models. To go beyond linear in the online setting, nonparametric methods are of interest due to their universality and ability to stably incorporate new information via convexity or Bayes's rule.

The field of machine learning has undergone radical transformations during the last decade. These transformations, which have been fueled by our ability to collect and generate tremendous volumes of training data and leverage massive amounts of low-cost computing power, have led to an explosion in research activity in the field by academic and industrial researchers.

Linear time-invariant (LTI) systems play a fundamental role in signal processing. Continuity is an important property of LTI systems, without which many conclusions about LTI systems, such as convolution formula and commutative law, are not true in general. However, this concept does not receive as much attention as it should in the literature of signal processing.

The Moving Picture Experts Group (MPEG) is an International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) working group that develops media coding standards. These standards include a set of ontologies for the codification of intellectual property rights (IPR) information related to media.

Cache-aided communications have shown potential for substantial improvement in network performance, which goes far beyond that of traditional caching. Traditional caching (i.e., the bringing and storing of data closer to the end users) is only efficient when a significant portion of the popular files can be locally stored.

A new generation of exponentially more intelligent and capable robots is on the way, helped along by talented and imaginative engineers and heavy doses of signal processing. In fields spanning almost every aspect of human professional and personal life, robots are ready to perform tasks faster, better, and more efficiently than their human counterparts. Even major sports organizations are now looking into the possibility of replacing human referees and umpires with robot arbiters.

After more than two years, my term as editor-in-chief (EIC) of IEEE Signal Processing Magazine (SPM) is coming to an end in December 2020. I am looking forward to finishing out this year with a bang. Soon, the search will start for my replacement. In this editorial, I will provide a summary of the EIC’s job from my perspective, in case you are interested in applying.