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The Latest News, Articles, and Events in Signal Processing
The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.
In an effort to continue our programs and services during this difficult time, the SPS Awards Board is now accepting nominations for all Society level awards, from paper awards to the major society awards. Nominations are due by 1 September 2021.
Dong Yu is an IEEE Fellow, ISCA Fellow, and an ACM distinguished scientist. He is currently taking the role of a distinguished scientist and vice general manager at Tencent AI Lab. Prior to joining Tencent America in 2017, he was a principal researcher at the speech and dialog research group, Microsoft Research (Redmond), Microsoft, where he joined in 1998.
The IEEE Signal Processing Society has developed guidelines related to SPS Chapter social media and Chapter Activities.
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.
Benefiting from the powerful discriminative feature learning capability of convolutional neural networks (CNNs), deep learning techniques have achieved remarkable performance improvement for the task of salient object detection (SOD) in recent years.
While current research on multimedia is essentially dealing with the information derived from our observations of the world, internal activities inside human brains, such as imaginations and memories of past events etc., could become a brand new concept of multimedia, for which we coin as “brain-media”.
Optimal rank selection is an important issue in tensor decomposition problems, especially for Tensor Train (TT) and Tensor Ring (TR) (also known as Tensor Chain) decompositions. In this paper, a new rank selection method for TR decomposition has been proposed for automatically finding near-optimal TR ranks, which result in a lower storage cost, especially for tensors with inexact TT or TR structures.
The emergence of big data and the multidimensional nature of wireless communication signals present significant opportunities for exploiting the versatility of tensor decompositions in associated data analysis and signal processing. The uniqueness of tensor decompositions, unlike matrix-based methods, can be guaranteed under very mild and natural conditions.
The papers in this special section focus on tensor decomposition for signal processing and machine learning. Tensor decomposition, also called tensor factorization, is useful for representing and analyzing multi-dimensional data. Tensor decompositions have been applied in signal processing applications (speech, acoustics, communications, radar, biomedicine), machine learning (clustering, dimensionality reduction, latent factor models, subspace learning), and well beyond.
We study distributed filtering for a class of uncertain systems over corrupted communication channels. We propose a distributed robust Kalman filter with stochastic gains, through which upper bounds of the conditional mean square estimation errors are calculated online.
In this paper, a smart pilot sequence assignment method is proposed to minimize inter-cell interference generated in a massive multi-input multi-output (MIMO) system due to pilot contamination in uplink TDD (Time Division Duplex) mode. The proposed method employs a zero-one integer linear programming method as the assignment algorithm.
Aalto University is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 11 000 students and a staff of more than 4000, of which 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness in the future as well.
The Department of Neurosurgery seeks a talented postdoctoral research associate to study the neurophysiology of sleep in human subjects, within the combined translational research efforts of Aviva Abosch, MD, PhD, Professor and Chair, Department of Neurosurgery, University of Nebraska Medical Center (UNMC), and Stephen Gliske, PhD, Assistant Professor, Department of Neurosurgery, and Co-Director of the MEG Program, UNMC.
Autonomous on-board drone navigation (i.e., without human intervention) in inaccessible environments is a fundamental challenge. The goal in this project is to develop novel machine learning algorithms for autonomous drone navigation in outdoor environments including localization and synchronization for BVLOS (beyond visual line of sight) scenarios and/or GPS-denied environments, by utilizing RF signals from fixed ground stations and/or in collaboration with other drones.
Title: Sparse predictive models for the analysis and classification of pathological speech
Duration: from 01/11/2021 to 31/12/2022 (could be extended to an advanced position)
Digital Voice Systems, Inc. (DVSI) is seeking a qualified Speech Research & Development Engineer at our office in Westford, MA. This is a great opportunity to join our team of world class engineers in designing high quality voice compression technology that is implemented in hundreds of millions of telecommunication systems world-wide.
At this time, we are extending the Editor-in-Chief nomination deadline for the following journals: IEEE/ACM Transactions on Audio, Speech, and Language Processing, IEEE Transactions on Computational Imaging, and IEEE Transactions on Information Forensics and Security. Nomination are due by 23 April 2023.
Lecture Date: May 25, 2021 -- Virtual Lecture
Chapter: Madras
Chapter Chair: S. Salivahanan
Topic: Making sense out of restless brain activity with computational neuroimaging
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