New Trends in Time–Frequency Signal Analysis and Processing
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: 31 July 2025 | Viewed by 428
Special Issue Editors
Interests: encompass various areas; including signal processing; time-frequency signal analysis; compressive sensing; information theory; electroencephalogram
Special Issue Information
Dear Colleagues,
Time–frequency signal analysis (TFSA) is a critical and advanced field in modern signal processing, extending beyond traditional Fourier transform to offer insights into the temporal and spectral characteristics of non-stationary signals. Given the diversity of signals in real-world applications, where the nature and behavior of signals are often unknown, there remain significant challenges in extracting useful information while successfully suppressing undesired interference and noise. Amidst the diverse methods and algorithms developed over the years, rapidly evolving technology is paving the way for new trends and potential solutions to real-world applications that demand innovative and effective approaches.
This Special Issue seeks high-quality submissions that present novel mathematical frameworks, advanced computational algorithms, and innovative applications of TFSA. Topics of interest include, but are not limited to, enhanced time–frequency representations; adaptive and robust signal processing techniques; the integration of machine learning paradigms; and novel applications in the Internet of Things (IoT), healthcare diagnostics, and environmental sensing. We particularly welcome papers that present interdisciplinary approaches that improve current methodologies and demonstrate significant advancements in the accuracy, efficiency, and interpretability of signal analysis. Contributions that bridge the gap between theory and practice, offering practical solutions to complex real-world problems, are highly encouraged.
Dr. Vedran Jurdana
Dr. Franck Badets
Guest Editors
Manuscript Submission Information
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Keywords
- enhanced time–frequency representations
- adaptive and robust signal processing techniques
- the integration of machine learning paradigms
- novel applications in the Internet of Things (IoT), healthcare diagnostics, and environmental sensing
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