From Circuits to Systems: Embedded and FPGA-Based Applications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".
Deadline for manuscript submissions: 15 July 2026 | Viewed by 12
Special Issue Editor
Interests: neural network accelerator; network protocol offloading; post-quantum cryptography (PQC); reconfigurable computing and VLSI SoC design
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Embedded systems and Field-Programmable Gate Arrays (FPGAs) have long been recognized as powerful platforms for delivering low-latency, energy-efficient, and highly customizable acceleration solutions. Their inherent flexibility, parallelism, and hardware-level optimization have enabled significant advances in traditional domains such as signal processing, industrial control, and communication infrastructure. However, the landscape of computing is rapidly evolving. With the emergence of data-intensive artificial intelligence workloads, large-scale computational tasks, high-speed network processing, and increasingly complex security requirements, new challenges arise in fully exploiting the capabilities of embedded platforms and FPGAs. These developments call for innovative design methodologies, scalable architectures, and domain-specialized accelerators that bridge circuit-level optimization with system-level performance demands.
The aim of this Special Issue, “From Circuits to Systems: Embedded and FPGA-Based Applications”, is to provide a platform for presenting recent advances, design methodologies, architectures, and practical implementations that push the frontier of FPGA-based and embedded-system research. We encourage contributions that demonstrate how emerging technologies such as machine learning, privacy-preserving computation, reconfigurable accelerators, and secure communication protocols can be efficiently produced and deployed on FPGA or embedded platforms.
This Special Issue welcomes original research articles, innovative designs, and comprehensive surveys. Topics of interest include, but are not limited to the following:
- FPGA-based acceleration for machine learning, deep learning, and data-intensive AI workloads;
- Hardware architectures for privacy-preserving computation, secure protocols, and cryptographic algorithms;
- High-performance and low-latency FPGA designs for networking, communication, and edge processing;
- Reconfigurable computing architectures and heterogeneous SoC/FPGA platforms;
- Hardware/software co-design methodologies for embedded and FPGA-based systems;
- Custom domain-specific accelerators and scalable FPGA computing architectures;
- Real-time signal, image, and video processing on embedded or FPGA platforms;
- Energy-efficient, low-power, and thermal-aware designs for reconfigurable hardware;
- Reliability, safety, and security mechanisms in embedded and reconfigurable systems;
- Embedded and FPGA-based solutions for edge computing, IoT, and autonomous systems;
- High-speed interconnects, memory architectures, and data movement optimization in FPGA systems;
- Emerging applications of FPGAs in robotics, smart sensing, biomedical systems, and high-performance computing.
Dr. Chen Yang
Guest Editor
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Keywords
- FPGA
- embedded systems
- edge and IoT systems
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