Inverse Problems and Optimization in Electromagnetic Systems
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".
Deadline for manuscript submissions: 15 June 2026 | Viewed by 105
Special Issue Editors
Interests: electromagnetic inverse scattering; computational electromagnetics
Interests: numerical methods in electromagnetics; EM theory
Special Issue Information
Dear Colleagues,
Electromagnetic (EM) systems are foundational to modern technology, enabling advancements in wireless communications, medical diagnostics, remote sensing, and non-destructive material evaluation. The performance and innovation in these areas are increasingly dependent on our ability to solve two classes of challenging problems: inverse problems and optimization problems. Inverse problems seek to determine the intrinsic properties or geometry of an object from external field measurements, while optimization problems aim to find the best possible design parameters to achieve a desired performance.
This Special Issue, "Inverse Problems and Optimization in Electromagnetic Systems," will focus on the latest theoretical advancements, novel computational algorithms, and pioneering applications in these interconnected fields. The scope is to create a comprehensive collection of high-quality research that addresses the entire spectrum of challenges, from mathematical formulation to practical implementation. We invite contributions on topics including, but not limited to, the following:
- Novel algorithms for EM inverse scattering (e.g., deep learning-based, deterministic, and stochastic methods).
- Advanced optimization techniques (e.g., topology optimization, genetic algorithms, swarm intelligence, multi-objective optimization) for the design of antennas, microwave circuits, and metamaterials.
- Applications in microwave and optical imaging, non-destructive testing, geophysical exploration, and biomedical diagnostics.
- Theoretical developments in regularization, uniqueness, and stability of EM inverse problems.
- The synergy between physics-based models and data-driven machine learning approaches.
- Hardware and software co-design and optimization for complex EM systems.
While many publications address electromagnetics or optimization separately, this Special Issue aims to uniquely bridge the gap between these disciplines. By presenting state-of-the-art research at this intersection, it will provide readers with a holistic view of current trends and future directions, fostering new collaborations and inspiring innovative solutions to real-world engineering challenges.
Prof. Dr. Kai Li
Dr. Huiran Zeng
Dr. Tong He
Guest Editors
Manuscript Submission Information
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Keywords
- inverse problems
- electromagnetic optimization
- computational electromagnetics
- antenna design
- metamaterials
- microwave imaging
- machine learning in electromagnetics
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