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The Latest News, Articles, and Events in Signal Processing
Position description: The department of Electrical Engineering at the Technion - Israel Institute of Technology invites researchers for a postdoctoral position in the area of machine learning for healthcare Medical Imaging and automotive radar. The selected candidate will work with Prof. Yonina Eldar at the SAMPL lab in collaboration with clinicians in Israel and USA.
Position description: The department of Electrical Engineering at the Technion - Israel Institute of Technology invites researchers for a postdoctoral position in the area of machine learning for healthcare Medical Imaging and automotive radar. The selected candidate will work with Prof. Yonina Eldar at the SAMPL lab in collaboration with clinicians in Israel and USA.
Speech, the expression of thoughts and feelings by articulating sounds, is an ability so taken for granted that few people bother to think about how complex and nuanced the process actually is. Yet, as more devices gain the ability to listen to and interpret what speakers are saying, speech and audiology technologies are attracting the interest of a growing number of academic researchers.
The Advertisers Index contained in this issue is compiled as a service to our readers and advertisers: the publisher is not liable for errors or omissions although every effort is made to ensure its accuracy. Be sure to let our advertisers know you found them through IEEE Signal Processing Magazine.
The future of computing is at crossroads. The technological advances that have sustained the exponential growth of computing performance over the last several decades are slowing and the roadmap for future advances is uncertain.
Smart CE systems (or, simplistically, smart electronic systems) are envisioned to be energy, security, and response smart. These three aspects and the design tradeoffs among them are the key for next-generation CE. Energy smart ensures minimal energy consumption that allows longer battery life and smaller energy bills.
Music is a ubiquitous and vital part of our lives. Thanks to the digital revolution in music distribution and storage, music has become one of the most popular categories of multimedia content. In general terms, music processing research contributes concepts, models, and algorithms that extend our capabilities of accessing, analyzing, manipulating, and creating music.
For our January 2019 issue, we cover recent patents granted in the area of face recognition. In one embodiment no. 10,162,999, a method includes accessing an image file associated with a first user of a communication system and detecting a face in an image corresponding to the image file.
IEEE SPS has built a streamlined mechanism for employers to add a job announcement by simply filling in a simple job opportunity submission Web form related to a particular TC field. To submit job announcements for a particular Technical Committee, the submission form can be found by visiting the page below and selecting a particular TC.
The IEEE Signal Processing Society is excited to launch the new Technical Pre-Approved Seasonal Schools Program, which will reward Chapters with a history of high quality programs and help increase the Society’s visibility and overall membership development of Students.
Please visit the Conferences and Events page on the IEEE Signal Processing Society website for Upcoming Lectures by Distinguished Lecturers.
The IEEE SPS congratulates the following SPS members who will receive the Society’s prestigious awards during ICASSP 2019 in Brighton, UK.
Submission Deadline: February 15, 2019
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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.
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.
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.
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.
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