Device Circuit Co Design Issues In Fets
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Device Circuit Co-Design Issues in FETs
This book provides an overview of emerging semiconductor devices and their applications in electronic circuits, which form the foundation of electronic devices. Device Circuit Co-Design Issues in FETs provides readers with a better understanding of the ever-growing field of low-power electronic devices and their applications in the wireless, biosensing, and circuit domains. The book brings researchers and engineers from various disciplines of the VLSI domain together to tackle the emerging challenges in the field of engineering and applications of advanced low-power devices in an effort to improve the performance of these technologies. The chapters examine the challenges and scope of FinFET device circuits, 3D FETs, and advanced FET for circuit applications. The book also discusses low-power memory design, neuromorphic computing, and issues related to thermal reliability. The authors provide a good understanding of device physics and circuits, and discuss transistors based on the new channel/dielectric materials and device architectures to achieve low-power dissipation and ultra-high switching speeds to fulfill the requirements of the semiconductor industry. This book is intended for students, researchers, and professionals in the field of semiconductor devices and nanodevices, as well as those working on device-circuit co-design issues.
Microwave Devices and Circuits for Advanced Wireless Communication
This book offers a comprehensive overview of design and analysis of microwave devices and circuits for 5G and beyond wireless communication systems. It focuses on modern microwave antennas, filters, metamaterials, and MIMO systems. It includes a design approach based on Artificial Intelligence and the practical use of microwave devices and circuits in commercial, medical, and military applications. Microwave Devices and Circuits for Advanced Wireless Communications: Design and Analysis explores the performance of microwave devices and circuits by highlighting the difficulties encountered by researchers and designers such as latency, interoperability, wireless coexistence, data streaming, safety, security, and privacy. The book explores the most important aspects of antenna design, including radiation pattern control, impedance matching with bandwidth improvement, and gain enhancement. It also examines different categories of metasurfaces, including frequency-selective surfaces (FSS) and electromagnetic bandgap (EBG) structures, and their distinct roles in antenna design. Additionally, the book examines concepts such as ultra-wideband (UWB) radar for 5G millimeter wave applications, and advanced techniques such as synthetic aperture radar (SAR), beam-forming, compressed sensing, and diffraction tomography for enabling high-resolution imaging across wider application areas. The authors also present an overview on applying machine learning (ML) techniques to advanced wireless communication for signal-processing tasks such as signal denoising, equalization, and modulation recognition. They then discuss the potential significance of UAV communication systems in achieving seamless connection, quality of service (QoS), as well as the difficulties and potential remedies involved in building dependable networks using UAVs. Throughout the book the authors offer a critical assessment of the strengths and limitations of each topic and approach presented, thus providing valuable guidance for future research in this exciting field. This book will be helpful for graduate students, researchers, and engineers working in the area of design and reliability of circuits for microwave and communication systems.
Advancing VLSI through Machine Learning
Author: Abhishek Narayan Tripathi
language: en
Publisher: CRC Press
Release Date: 2025-03-31
This book explores the synergy between very large-scale integration (VLSI) and machine learning (ML) and its applications across various domains. It investigates how ML techniques can enhance the design and testing of VLSI circuits, improve power efficiency, optimize layouts, and enable novel architectures. This book bridges the gap between VLSI and ML, showcasing the potential of this integration in creating innovative electronic systems, advancing computing capabilities, and paving the way for a new era of intelligent devices and technologies. Additionally, it covers how VLSI technologies can accelerate ML algorithms, enabling more efficient and powerful data processing and inference engines. It explores both hardware and software aspects, covering topics like hardware accelerators, custom hardware for specific ML tasks, and ML-driven optimization techniques for chip design and testing. This book will be helpful for academicians, researchers, postgraduate students, and those working in ML-driven VLSI.