Modelling Methodologies in Analogue Integrated Circuit Design provides a holistic view of modelling for analogue, high frequency, mixed signal, and heterogeneous systems for designers working towards improving efficiency, reducing design times, and addressing the challenges of representing aging, variability, and other technical challenges at the nanometre scale. The book begins by introducing the concept, history, and development of circuit design up to the present day. The first half of the book then covers various modelling methodologies and addresses model accuracy and verification. Modelling approaches are introduced theoretically along with simple examples to demonstrate the concepts. Later chapters approach modelling from the application point of view, including case studies from the vast domain of integrated circuit design. Topics covered include response surface modeling; machine learning; data-driven and physics-based modeling; verification of modelling: metrics and methodologies; an overview of modern, automated analog circuit modeling methods; machine learning techniques for the accurate modeling of integrated inductors for RF applications; modeling of variability and reliability in analog circuits; modeling of pipeline ADC functionality and non-idealities; power systems modelling; case study - an efficient design and layout of a 3D accelerometer by automated synthesis; and sensing schemes for spintronic resistive memories.

Advances in Imaging and Electron Physics, Volume 227 in the Advances in Imaging and Electron Physics series, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

Cerium Oxide (CeO2): Synthesis, Properties and Applications provides an updated and comprehensive account of the research in the field of cerium oxide based materials. The book is divided into three main blocks that deal with its properties, synthesis and applications. Special attention is devoted to the growing number of applications of ceria based materials, including their usage in industrial and environmental catalysis and photocatalysis, energy production and storage, sensors, cosmetics, radioprotection, glass technology, pigments, stainless steel and toxicology. A brief historical introduction gives users background, and a final chapter addresses future perspectives and outlooks to stimulate future research. The book is intended for a wide audience, including students, academics and industrial researchers working in materials science, chemistry and physics.

The application of artificial intelligence technology to 5G wireless communications is now appropriate to address the design of optimized physical layers, complicated decision-making, network management, and resource optimization tasks within networks. In exploring 5G wireless technologies and communication systems, artificial intelligence is a powerful tool and a research topic with numerous potential fields of application that require further study. Applications of Artificial Intelligence in Wireless Communication Systems explores the applications of artificial intelligence for the optimization of wireless communication systems, including channel models, channel state estimation, beamforming, codebook design, signal processing, and more. Covering key topics such as neural networks, deep learning, and wireless systems, this reference work is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Industry 4.0 and the subsequent automation and digitalization of processes, including the tighter integration of machine-machine and human-machine intercommunication and collaboration, is adding additional complexity to future systems design and the capability to simulate, optimize, and adapt. Current solutions lack the ability to capture knowledge, techniques, and methods to create a sustainable and intelligent nerve system for enterprise systems. With the ability to innovate new designs and solutions, as well as automate processes and decision-making capabilities with heterogenous and holistic views of current and future challenges, there can be an increase in productivity and efficiency through sustainable automation. Therefore, better understandings of the underpinning knowledge and expertise of sustainable automation that can create a sustainable cycle that drives optimal automation and innovation in the field is needed Driving Innovation and Productivity Through Sustainable Automation enhances the understanding and the knowledge for the new ecosystems emerging in the Fourth Industrial Revolution. The chapters provide the knowledge and understanding of current challenges and new capabilities and solutions having been researched, developed, and applied within the industry to drive sustainable automation for innovation and productivity. This book is ideally intended for managers, executives, IT specialists, practitioners, stakeholders, researchers, academicians, and students who are interested in the current research on sustainable automation.

III-Nitride Electronic Devices, Volume 102, emphasizes two major technical areas advanced by this technology: radio frequency (RF) and power electronics applications. The range of topics covered by this book provides a basic understanding of materials, devices, circuits and applications while showing the future directions of this technology. Specific chapters cover Electronic properties of III-nitride materials and basics of III-nitride HEMT, Epitaxial growth of III-nitride electronic devices, III-nitride microwave power transistors, III-nitride millimeter wave transistors, III-nitride lateral transistor power switch, III-nitride vertical devices, Physics-Based Modeling, Thermal management in III-nitride HEMT, RF/Microwave applications of III-nitride transistor/wireless power transfer, and more.

2D Semiconductor Materials and Devices reviews the basic science and state-of-art technology of 2D semiconductor materials and devices. Chapters discuss the basic structure and properties of 2D semiconductor materials, including both elemental (silicene, phosphorene) and compound semiconductors (transition metal dichalcogenide), the current growth and characterization methods of these 2D materials, state-of-the-art devices, and current and potential applications.

Graphene Extraction from Waste: A Sustainable Synthesis Approach for Graphene and its Derivatives introduces readers to strategies of graphene extraction from waste, an important advance in graphene material development to support the low-cost and large-scale production of this valuable material. The book compares the various green synthesis routes for graphene materials and its derivatives, with a view on environmental consequences, cost-effectiveness, scalability, possible health hazards and toxicity. Other sections discuss different categories of waste, such as plastic waste, agricultural waste and household waste and the specific considerations of deriving graphene from these sources. Throughout the book, attention is paid to the potential applications of graphene-derived from waste, including challenges and emerging strategies. The book is suitable for researchers and practitioners in research and development in industry who work in the disciplines of materials science and engineering, green chemistry and sustainability.

Metal Halide Perovskites for Generation, Manipulation and Detection of Light covers the current state and future prospects of lead halide perovskite photonics and photon sources, both from an academic and industrial point-of-view. Advances in metal halide perovskite photon sources (lasers) based on thin films, microcrystals and nanocrystals are comprehensively reviewed, with leading experts contributing current advances in theory, fundamental concepts, fabrication techniques, experiments and other important research innovations. This book is suitable for graduate students, researchers, scientists and engineers in academia and R&D in industry working in the disciplines of materials science and engineering.

Advances in Imaging and Electron Physics, Volume 212, merges two long-running serials, Advances in Electronics and Electron Physics and Advances in Optical and Electron Microscopy. The series features extended articles on the physics of electron devices (especially semiconductor devices), particle optics at high and low energies, microlithography, image science, digital image processing, electromagnetic wave propagation, electron microscopy and the computing methods used in all these domains.

Handbook of Robotic and Image-Guided Surgery provides state-of-the-art systems and methods for robotic and computer-assisted surgeries. In this masterpiece, contributions of 169 researchers from 19 countries have been gathered to provide 38 chapters. This handbook is 744 pages, includes 659 figures and 61 videos. It also provides basic medical knowledge for engineers and basic engineering principles for surgeons. A key strength of this text is the fusion of engineering, radiology, and surgical principles into one book.

Bioelectronics and Medical Devices: From Materials to Devices-Fabrication, Applications and Reliability reviews the latest research on electronic devices used in the healthcare sector, from materials, to applications, including biosensors, rehabilitation devices, drug delivery devices, and devices based on wireless technology. This information is presented from the unique interdisciplinary perspective of the editors and contributors, all with materials science, biomedical engineering, physics, and chemistry backgrounds. Each applicable chapter includes a discussion of these devices, from materials and fabrication, to reliability and technology applications. Case studies, future research directions and recommendations for additional readings are also included. The book addresses hot topics, such as the latest, state-of the-art biosensing devices that have the ability for early detection of life-threatening diseases, such as tuberculosis, HIV and cancer. It covers rehabilitation devices and advancements, such as the devices that could be utilized by advanced-stage ALS patients to improve their interactions with the environment. In addition, electronic controlled delivery systems are reviewed, including those that are based on artificial intelligences.

A comprehensive exploration of the control schemes of human-robot interactions In Human-Robot Interaction Control Using Reinforcement Learning, an expert team of authors delivers a concise overview of human-robot interaction control schemes and insightful presentations of novel, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control and reinforcement learning before moving on to describe the typical environment model. The authors also describe some of the most famous identification techniques for parameter estimation. Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical treatments and demonstrations that facilitate the understanding of control schemes and algorithms. It also describes stability and convergence analysis of human-robot interaction control and reinforcement learning based control. The authors also discuss advanced and cutting-edge topics, like inverse and velocity kinematics solutions, H2 neural control, and likely upcoming developments in the field of robotics. Readers will also enjoy: A thorough introduction to model-based human-robot interaction control Comprehensive explorations of model-free human-robot interaction control and human-in-the-loop control using Euler angles Practical discussions of reinforcement learning for robot position and force control, as well as continuous time reinforcement learning for robot force control In-depth examinations of robot control in worst-case uncertainty using reinforcement learning and the control of redundant robots using multi-agent reinforcement learning Perfect for senior undergraduate and graduate students, academic researchers, and industrial practitioners studying and working in the fields of robotics, learning control systems, neural networks, and computational intelligence, Human-Robot Interaction Control Using Reinforcement Learning is also an indispensable resource for students and professionals studying reinforcement learning.

Dynamic System Modeling & Analysis with MATLAB & Python A robust introduction to the advanced programming techniques and skills needed for control engineering In Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers, accomplished control engineer Dr. Jongrae Kim delivers an insightful and concise introduction to the advanced programming skills required by control engineers. The book discusses dynamic systems used by satellites, aircraft, autonomous robots, and biomolecular networks. Throughout the text, MATLAB and Python are used to consider various dynamic modeling theories and examples. The author covers a range of control topics, including attitude dynamics, attitude kinematics, autonomous vehicles, systems biology, optimal estimation, robustness analysis, and stochastic system. An accompanying website includes a solutions manual as well as MATLAB and Python example code. Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers provides readers with a sound starting point to learning programming in the engineering or biology domains. It also offers: A thorough introduction to attitude estimation and control, including attitude kinematics and sensors and extended Kalman filters for attitude estimation Practical discussions of autonomous vehicles mission planning, including unmanned aerial vehicle path planning and moving target tracking Comprehensive explorations of biological network modeling, including bio-molecular networks and stochastic modeling In-depth examinations of control algorithms using biomolecular networks, including implementation Dynamic System Modeling & Analysis with MATLAB & Python: For Control Engineers is an indispensable resource for advanced undergraduate and graduate students seeking practical programming instruction for dynamic system modeling and analysis using control theory.