Special Session II: Advances in Adaptive Signal Processing: From Classical Algorithms to Intelligent Learning Systems


Adaptive signal processing is a fundamental and rapidly evolving discipline that enables intelligent and real-time adjustment of system parameters in response to dynamic environments. It plays a critical role in a wide range of applications, including communications, radar, sonar, biomedical engineering, and multimedia systems. With the emergence of new computational paradigms such as artificial intelligence and machine learning, adaptive signal processing has gained even greater potential to address complex and high-dimensional problems in sensing, interpretation, and decision-making.

This Special Issue aims to present cutting-edge research and innovative applications in the field of adaptive signal processing. We welcome contributions that introduce new theories, algorithms, architectures, and practical implementations. Topics of interest include, but are not limited to:

• Adaptive filtering and system identification
• Adaptive beamforming and array processing
• Statistical and learning-based adaptive algorithms
• Adaptive spectral estimation and time-frequency analysis
• Robust adaptive signal processing
• Adaptive methods for radar, sonar, and wireless communications
• Machine learning and deep learning for adaptive processing
• Real-time implementation and hardware acceleration
• Adaptive techniques for sensor networks and IoT systems
• Applications in biomedical, audio, and multimedia signal processing
• Adaptive clutter, noise, and interference suppression
• Cognitive dynamic systems and reinforcement learning for adaptation

We invite researchers and practitioners from academia and industry to submit original research articles and comprehensive reviews that demonstrate significant advances in adaptive signal processing theory and applications.

Submission Method


Electronic Submission System (.pdf) (Please select and click Special Session 2: Advances in Adaptive Signal Processing: From Classical Algorithms to Intelligent Learning Systems to submit.)

Organizer


Guobing Qian, Associate Professor, Master's Supervisor, IEEE Senior Member, and Senior Member of the Chinese Institute of Electronics. He received the Ph.D. degree in signal and information processing from the University of Electronic Science and Technology of China in December, 2015. Now, he is working in the College of Electronic and Information Engineering, Southwest University. His current research mainly focuses on adaptive filter, adaptive signal processing, and so on.

 

 

Sheng Zhang received the B.S. degree in Information and Computing Science from the College of Mathematics and Information Sciences, North China University of Water Resources and Electric Power, Zhengzhou, China, in 2010, and the Ph.D. degree in signal and information processing from Southwest Jiaotong University, Chengdu, China, in 2016. Since 2017, he has been with the School of Information Science and Technology, Southwest Jiaotong University, where he is currently an Associate Professor. He has published more than ten papers in IEEE Transactions on Signal Processing over the past five years. His research interests include distributed adaptation and learning theories.

 

 

Ying-Ren Chien (Senior Member, IEEE) received the B.S. degree in electronic engineering from the National Yunlin University of Science and Technology, Douliu, Taiwan, in 1999, and the M.S. degree in electrical engineering and the Ph.D. degree in communication engineering from National Taiwan University, Taipei, Taiwan, in 2001 and 2009, respectively.
He joined Department of Electrical Engineering, National Ilan University (NIU), Yilan City, Taiwan, from 2012 to 2025. He has been promoted to Full Professor since 2018; he served as the Chair at NIU from 2018 to 2025. Since 2025, he has been with Department of Electronic Engineering, National Taipei University of Technology (NTUT), Taipei, where he is currently a Full Professor. His research interests are consumer electronics, multimedia denoising algorithms, adaptive signal processing theory, active noise control, machine learning, the Internet of Things, and interference cancellation.
Dr. Chien received best paper awards, including ICCCAS 2007, ROCKLING 2017, and IEEE ISPACS 2021. He was presented with the IEEE CESoc/CTSoc Service Awards in 2019, NSC/MOST Special Outstanding Talent Award in 2021, 2023, and 2024, Excellent Research-Teacher Award in 2018 and 2022, and Excellent Teaching Award in 2021. From 2023 to 2024, he was the Vice Chair of IEEE Consumer Technology Society (CTSoc) Virtual Reality, Augmented Reality, and Metaverse (VAM) Technical Committee (TC). Since 2025, he has been the Secretary of IEEE CTSoc Audio/Video Sytems and Signal Processing (AVS) TC. He is currently an Associate Editor of IEEE Transactions on Consumer Electronics.