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Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques.

Features:

Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation

This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques.

Features:

Provides the details of state-of-the-art machine learning methods used in VLSI design Discusses hardware implementation and device modeling pertaining to machine learning algorithms Explores machine learning for various VLSI architectures and reconfigurable computing Illustrates the latest techniques for device size and feature optimization Highlights the latest case studies and reviews of the methods used for hardware implementation

This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques.Features:Provides the details of state-of-the-art machine learning methods used in VLSI designDiscusses hardware implementation and device modeling pertaining to machine learning algorithmsExplores machine learning for various VLSI architectures and reconfigurable computingIllustrates the latest techniques for device size and feature optimizationHighlights the latest case studies and reviews of the methods used for hardware implementationThis book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learning–based methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques.Features:Provides the details of state-of-the-art machine learning methods used in VLSI designDiscusses hardware implementation and device modeling pertaining to machine learning algorithmsExplores machine learning for various VLSI architectures and reconfigurable computingIllustrates the latest techniques for device size and feature optimizationHighlights the latest case studies and reviews of the methods used for hardware implementationThis book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.

This book provides practical solutions for delay and power reduction for on-chip interconnects and buses.  It provides an in depth description of the problem of signal delay and extra power consumption, possible solutions for delay and glitch removal, while considering the power reduction of the total system.  Coverage focuses on use of the Schmitt Trigger as an alternative approach to buffer insertion for delay and power reduction in VLSI interconnects. In the last section of the book, various bus coding techniques are discussed to minimize delay and power in address and data buses.

This book provides practical solutions for delay and power reduction for on-chip interconnects and buses.  It provides an in depth description of the problem of signal delay and extra power consumption, possible solutions for delay and glitch removal, while considering the power reduction of the total system.  Coverage focuses on use of the Schmitt Trigger as an alternative approach to buffer insertion for delay and power reduction in VLSI interconnects. In the last section of the book, various bus coding techniques are discussed to minimize delay and power in address and data buses.

This book provides practical solutions for delay and power reduction for on-chip interconnects and buses.  It provides an in depth description of the problem of signal delay and extra power consumption, possible solutions for delay and glitch removal, while considering the power reduction of the total system.  Coverage focuses on use of the Schmitt Trigger as an alternative approach to buffer insertion for delay and power reduction in VLSI interconnects. In the last section of the book, various bus coding techniques are discussed to minimize delay and power in address and data buses.

Develop real-world interactive physical computing applications using the Micro:bit with more than 100 MicroPython examples with circuit diagramsKey FeaturesExplore hardware programming and leverage the power of the BBC Micro:bit and MicroPythonBuild real-life creative projects step by step with each chapter increasing in complexity and interactivityLearn the features of the Micro:bit and how to interface it with electronic components through circuits and code examplesBook DescriptionThis book is a one-stop guide for learning BBC Micro:bit with MicroPython, exploring many hardware components and programming techniques to provide detailed insights into developing practical applications with the Micro:bit. It will also show you how hardware components can be manipulated using a combination of Micro:bit and MicroPython for developing practical projects. BBC Micro:bit in Practice will help you gain a holistic understanding of the BBC Micro:bit platform and MicroPython programming, guiding you through mini projects aimed at developing practical knowledge of circuit design and writing programs. You’ll learn how to write programs for working with built-in LEDs and buttons, interfacing external LEDs, buttons, motors, buzzers, and much more. You’ll also work with built-in radio, speakers, accelerometer, and a compass. You’ll dive into concepts related to the Micro:bit filesystem, interfacing external displays, and working with libraries in detail before exploring sewable circuits and wearable technology.After reading this Micro:bit book, you’ll understand how to apply principles in electronics and MicroPython to create interesting real-life projects from scratch.What you will learnExplore the essentials of the BBC Micro:bit, its hardware specifications, and versionsProgram built-in and external LEDs and buttonsProgram external LED-based displays, buzzers, and stepper motorsUse analog input and pulse width modulation to drive a servo motorDetect gestures with internal sensors such as accelerometer, compass, and magnetometerWork on projects with built-in features such as music, speech, radio, and filesystemExplore the advanced features of the Micro:bitWho this book is forThis book is for anyone who wants to use the combination of MicroPython and the BBC Micro:bit for building exciting real-life projects. Engineers, researchers, hobbyists, and technology instructors working in areas such as embedded systems, electronics, software development, IoT, robotics, teaching, and training will find this book useful for building projects. Prior experience with building basic electronic circuits and any programming language, not necessarily MicroPython, will be helpful.