Artificial Intelligence and Advanced Signal Processing Techniques and Their Applications

Dear Colleagues,

In the contemporary technological landscape, artificial intelligence (AI) and advanced signal processing techniques have emerged as the cornerstones of innovation across numerous domains. Advanced signal processing serves as the bedrock for acquiring, filtering, analyzing, and interpreting various types of signals, including audio, video, sensor, and communication signals. Meanwhile, AI—with its powerful capabilities in machine learning, deep learning, and natural language processing—has revolutionized the way we handle and make sense of these signals.

The integration of AI and advanced signal processing techniques has led to remarkable breakthroughs. It enables intelligent signal analysis, accurate pattern recognition, and efficient data-driven decision-making. For instance, in healthcare, AI-enhanced signal processing can detect early signs of diseases from physiological signals. In autonomous vehicles, it helps in perceiving the environment through radar, lidar, and camera signals. In telecommunications, it improves the quality of data transmission and reception.

However, this convergence also brings about a series of challenges. Pressing issues include the need to ensure the accuracy and reliability of AI-based signal processing models, dealing with the increasing complexity of signal data, and addressing security and privacy concerns in signal-related AI applications.

This Special Issue is dedicated to exploring novel approaches, methodologies, and frameworks that address the opportunities and challenges encountered at the intersection of AI and advanced signal processing techniques and their applications. It aims to provide a platform for researchers, practitioners, and experts in these fields to share their latest findings, exchange ideas, and drive the advancement of the state of the art. By thoroughly examining the complex relationship between AI and signal processing, this Special Issue endeavors to contribute significantly to the development of intelligent and efficient signal-processing systems, ultimately fostering the widespread adoption of these technologies in diverse industries.

We welcome high-quality original research and review articles in this area. We also encourage submissions related to ongoing research projects, case studies, and practical applications. We will publish selected papers from the 2025 International Conference on Neural Computing for Advanced Applications (https://aaci.org.hk/ncaa2025/). This Special Issue encompasses a wide range of topics related to AI and advanced signal processing techniques and their applications. These include but are not limited to the following:

• AI-based signal feature extraction and classification algorithms.
• Deep learning models for signal denoising, enhancement, and restoration.
• Reinforcement learning applications in signal processing optimization.
• Signal processing for computer vision tasks such as object detection, recognition, and tracking.
• Speech signal processing using AI, including speech recognition, synthesis, and emotion analysis.
• Sensor signal processing in IoT (Internet of Things) with the aid of AI techniques.
• Biomedical signal processing for medical diagnosis and treatment using AI - enhanced methods.
• Adaptive signal processing based on AI algorithms for dynamic environments.
• Multimodal signal fusion and processing using AI for comprehensive data analysis.
• AI-driven signal compression techniques for efficient data storage and transmission.
• Security and privacy preservation in AI-based signal processing systems.
• Explainable AI in signal processing for better understanding and trust.
• Application of AI and advanced signal processing in smart grids, smart cities, and environmental monitoring.
• Application of AI and advanced signal processing in machinery fault detection and magnetic target detection.
• Advanced signal processing techniques for 5G/6G wireless communication and beyond.
• Real-time signal processing with AI for time-critical applications.

Dr. Wangpeng He
Dr. Binqiang Chen
Dr. Yizhen Peng
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence
• advanced signal processing techniques
• deep learning
• machine learning
• industrial applications