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Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

The authors of [1], which was published in the November 2017 issue of IEEE Signal Processing Magazine, wish to add an acknowledgment to their article. The acknowledgment is as follows: This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (number 2016R1A2B2014525) and by a grant from the National Science Foundation (IIS-1116656) awarded to Alan C. Bovik.

Section: Publications & Resources

Publication: IEEE Transactions on Signal Processing

Incorporating graphs in the analysis of multivariate signals is becoming a standard way to understand the interdependency of activity recorded at different sites. The new research frontier in this direction includes the important problem of how to assess dynamic changes of signal activity. We address this problem in a novel way by defining the graph-variate signal alongside methods for its analysis.

Section: Publications & Resources

Publication: IEEE Transactions on Signal Processing

Various signal processing applications can be expressed as large-scale optimization problems with a composite objective structure, where the Lipschitz constant of the smooth part gradient is either not known, or its local values may only be a fraction of the global value. The smooth part may be strongly convex as well. The algorithms capable of addressing this problem class in its entirety are black-box accelerated first-order methods, related to either Nesterov's Fast Gradient Method or the Accelerated Multistep Gradient Scheme, which were developed and analyzed using the estimate sequence mathematical framework.

Section: Publications & Resources

Publication: IEEE Transactions on Signal Processing

Recently, many sparse arrays have been proposed to increase the number of degrees of freedom for direction of arrival (DoA) estimation especially for circular signals. Though many practical signals are noncircular, still the properties of noncircularity are hardly exploited in the design of sparse linear arrays. A new array geometry for noncircular signals, which significantly increases the aperture of the virtual array, has been proposed in this paper. 

Section: Publications & Resources

Publication: IEEE Transactions on Signal Processing

Linear regression models contaminated by Gaussian noise (inlier) and possibly unbounded sparse outliers are common in many signal processing applications. Sparse recovery inspired robust regression (SRIRR) techniques are shown to deliver high-quality estimation performance in such regression models. Unfortunately, most SRIRR techniques assume a priori knowledge of noise statistics like inlier noise variance or outlier statistics like number of outliers.

Section: Publications & Resources

Publication: IEEE Transactions on Signal Processing

Distributed estimation fusion is concerned with the combination of local estimates from multiple distributed sensors to produce a fused result. In this paper, we characterize local estimates as posterior probability densities, and assume that they all belong to a parametric family. Our starting point is to consider this family as a Riemannian manifold by introducing the Fisher information metric.

Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

The title of this editorial is borrowed from a popular children’s lullaby from the 1800s, which reads “Twinkle, twinkle, little star, how I wonder what you are!” It reminds me of the vast expanse of unexplored space (and science) that lie before us.    The human race has always been fascinated by space - and who would not be? Its shining stars continually challenge us to get closer and unravel their mysteries.

Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

There have been three key revolutions in the way that research has become accessible: publishing, code, and data. The second and third revolutions are still taking place, particularly driven by the rise of machine-learning and artificial intelligence research in the last decade. When I started my research career in 1995, the World Wide Web was still in its infancy. The popular Netscape browser had just been launched. Search engines were not widely used. While many academics owned e-mail addresses, few had web pages. If they did, they were not kept current.

Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

The Bio-Imaging and Signal Processing Technical Committee (BISP-TC) of the IEEE Signal Processing Society (SPS) promotes activities in the broad technical areas of computerized image and signal processing with a clear focus on applications in biology and medicine.

Section: Publications & Resources

Publication: IEEE Signal Processing Magazine

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