This book provides readers with a comprehensive, state-of-the-art overview of approximate computing, enabling the design trade-off of accuracy for achieving better power/performance efficiencies, through the simplification of underlying computing resources. The authors describe in detail various efforts to generate approximate hardware systems, while still providing an overview of support techniques at other computing layers. The book is organized by techniques for various hardware components, from basic building blocks to general circuits and systems.

This book describes reliable and efficient design automation techniques for the design and implementation of an approximate computing system. The authors address the important facets of approximate computing hardware design - from formal verification and error guarantees to synthesis and test of approximation systems. They provide algorithms and methodologies based on classical formal verification, synthesis and test techniques for an approximate computing IC design flow. This is one of the first books in Approximate Computing that addresses the design automation aspects, aiming for not only sketching the possibility, but providing a comprehensive overview of different tasks and especially how they can be implemented.

This book presents various novel architectures for FPGA-optimized accurate and approximate operators, their detailed accuracy and performance analysis, various techniques to model the behavior of approximate operators, and thorough application-level analysis to evaluate the impact of approximations on the final output quality and performance metrics. As multiplication is one of the most commonly used and computationally expensive operations in various error-resilient applications such as digital signal and image processing and machine learning algorithms, this book particularly focuses on this operation. The book starts by elaborating on the various sources of error resilience and opportunities available for approximations on various layers of the computation stack. It then provides a detailed description of the state-of-the-art approximate computing-related works and highlights their limitations.

This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

Electric Motors and Drives is intended for non-specialist users of electric motors and drives, filling the gap between maths- and theory-based academic textbooks and the more prosaic 'handbooks', which provide useful detail but little opportunity for the development of real insight and understanding. The book explores all of the widely-used modern types of motor and drive, including conventional and brushless D.C., induction motors and servo drives, providing readers with the knowledge to select the right technology for a given job.The third edition includes additional diagrams and worked examples throughout. New topics include digital interfacing and control of drives, direct torque control of induction motors and current-fed operation in DC drives. The material on brushless servomotors has also been expanded.Austin Hughes' approach, using a minimum of maths, has established Electric Motors and Drives as a leading guide for electrical engineers and mechanical engineers, and the key to a complex subject for a wider readership, including technicians, managers and students. - Acquire knowledge of and understanding of the capabilities and limitations of motors and drives without struggling through unnecessary maths and theory - Updated material on the latest and most widely-used modern motors and drives, including brushless servomotors - New edition includes additional diagrams and worked examples throughout