The field of information theory - dating back to the seminal work by Claude E. Shannon in 1948 - is considered to be one of the landmark intellectual achievements of the 20^th century, underpinning advances in compression and communication of data that underpins the information age. In particular, information-theoretic methods have been used to illuminate fundamental limits and gauge the effectiveness of algorithms for various problems in statistical decision theory, data communications, data compression, security, and networking.

This webinar will provide an in-depth survey look into 40 years of cross-disciplinary academic and industrial research and development work on radar tracking systems, starting from the former implementations based on the α – β, the Kalman filter, and up to the modern implementations based on random set filters.

In recent years, the complexity of designing embedded signal processing systems for wireless communications has increased significantly based on the need to support increasing levels of operational flexibility and adaptivity, while also supporting increasing data rates and bandwidths.

This dissertation focuses on statistical signal processing theory and its applications to radar, complex-valued signal processing and model selection.

This year the Signal Processing Society identified 16 Chapters who exhibited excellence in many facets of chapter management, member recruitment, and activities.

The IEEE Signal Processing Society (SPS) Publications group is pleased to announce the launch of the IEEE SPS Author Survey. This automated survey is being delivered to the corresponding authors when their articles are final and published on IEEE Xplore®. 

Check back on the SPS website to keep up-to-date on upcoming Seasonal Schools! Are you looking to energize signal processing students, early stage researchers, and industry practitioners in your area? Consider hosting a Seasonal School for young engineers near you!

The IEEE Signal Processing Society continues to track emerging technical areas. As a result, the Society has decided to create two new SPS Technical Interest Profile (TIP) Code categories in the fields of Data Science and Autonomous Systems to keep pace with the expanding technical disciplines.