Upcoming Distinguish Lectures
1 June 2016
Please visit the Conferences and Events page on the IEEE Signal Processing Society website for upcoming Lectures by Distinguished Lecturers.
Read moreBriggs, GordonView Profile. (Tufts University), “Toward Dialogue and Reasoning Mechanisms to Enable More Natural and Socially-Appropriate Task-Based Human-Robot Interactions” (2016)
1 June 2016
Briggs, GordonView Profile.
Read moreSimek, Kyle LouisView Profile. (The University of Arizona), “Branching Gaussian process models for computer vision” (2016)
1 June 2016
Simek, Kyle LouisView Profile. (The University of Arizona), “Branching Gaussian process models for computer vision” (2016) Advisor: Jacobus Kobus…
Read moreIntroducing the SPS Resource Center
1 June 2016
In 2013, the IEEE Signal Processing Society (SPS) introduced SigView – our online portal of video tutorials in emerging signal processing topics…
Read moreRecent Patents in Signal Processing (June 2016) – medical imaging
1 June 2016
For our June 2016 issue, we cover recent patents dealing with hardware and signal processing issues of medical imaging.
Update from IFS-TC
1 June 2016
The Information Forensics and Security Technical Committee (IFS TC) reports on a special issue on spoofing and countermeasures for automatic speaker verification and a call for tutorials and special sessions at the WIFS 2016
Call for Nominations: Awards Board Chair
1 June 2016
The IEEE Signal Processing Society (SPS) invites nominations for the position of Awards Board Chair. The term for the Awards Board Chair position…
Read moreCall for Nominations: Chapter of the Year Award
1 June 2016
The IEEE Signal Processing Society Chapter of the Year Award will be presented for the sixth time in 2017. The award will be presented annually to a…
Read moreImportant Message Requiring Your Vote
1 June 2016
Rabab Ward President, IEEE Signal Processing Society
Read moreIssue on Structured Matrices in Signal and Data Processing
1 June 2016
The idea of representing a signal as a vector living in some linear vector space has borne tremendous fruit in signal processing: this viewpoint provides an encompassing framework for classical least-squares and subspace-based signal processing, and a language with which to model a signal’s structural properties.
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