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Biomimetic devices are designed and produced by materials, structures, and systems that are modelled on biological entities and processes. These devices are used to synthesize novel materials and their functions at the multiscale level for various applications. Molecular computing biological devices play a key role in the logical processing of the cellular machinery of all living organisms. This book includes information on both biomedical and technological applications of bioactive devices for hard tissue regeneration; design of chip-based disease diagnostic platforms; neuromorphic computing biomaterials that transfer techniques of neuroscience to a silicon chip; various top-down and bottom-up designs; and electrical characterization and transport mechanisms of DNA as nanowires.
This book describes machine learning-based new principles, methods of design and optimization of high-speed integrated circuits, included in one electronic system, which can exchange information between each other up to 128/256/512 Gbps speed. The efficiency of methods has been proven and is described on the examples of practical designs. This will enable readers to use them in similar electronic system designs. The author demonstrates newly developed principles and methods to accelerate communication between ICs, working in non-standard operating conditions, considering signal deviation compensation with linearity self-calibration. The observed circuit types also include but are not limited to mixed-signal, high performance heterogeneous integrated circuits as well as digital cores.
Examines the advantages of Embedded and FO-WLP technologies, potential application spaces, package structures available in the industry, process flows, and material challenges Embedded and fan-out wafer level packaging (FO-WLP) technologies have been developed across the industry over the past 15 years and have been in high volume manufacturing for nearly a decade. This book covers the advances that have been made in this new packaging technology and discusses the many benefits it provides to the electronic packaging industry and supply chain. It provides a compact overview of the major types of technologies offered in this field, on what is available, how it is processed, what is driving its development, and the pros and cons. Filled with contributions from some of the field's leading experts,Advances in Embedded and Fan-Out Wafer Level Packaging Technologies begins with a look at the history of the technology. It then goes on to examine the biggest technology and marketing trends. Other sections are dedicated to chip-first FO-WLP, chip-last FO-WLP, embedded die packaging, materials challenges, equipment challenges, and resulting technology fusions. Discusses specific company standards and their development results Content relates to practice as well as to contemporary and future challenges in electronics system integration and packaging Advances in Embedded and Fan-Out Wafer Level Packaging Technologies will appeal to microelectronic packaging engineers, managers, and decision makers working in OEMs, IDMs, IFMs, OSATs, silicon foundries, materials suppliers, equipment suppliers, and CAD tool suppliers. It is also an excellent book for professors and graduate students working in microelectronic packaging research.
Quality Electronic Design (QED)’s landscape spans a vast region where territories of many participating disciplines and technologies overlap. This book explores the latest trends in several key topics related to quality electronic design, with emphasis on Hardware Security, Cybersecurity, Machine Learning, and application of Artificial Intelligence (AI). The book includes topics in nonvolatile memories (NVM), Internet of Things (IoT), FPGA, and Neural Networks.
An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions. This two-volume handbook covers methods as well as applications. This first volume focuses on real-time control theory, data assimilation, real-time visualization, high-dimensional state spaces and interaction of different reduction techniques.
This book deals with the analysis and development of numerical methods for the time-domain analysis of multiphysical effects in superconducting circuits of particle accelerator magnets. An important challenge is the simulation of “quenching”, i.e. the transition of a material from the superconducting to the normally electrically conductive state. The book analyses complex mathematical structures and presents models to simulate such quenching events in the context of generalized circuit elements. Furthermore, it proposes efficient parallelized algorithms with guaranteed convergence properties for the simulation of multiphysical problems. Spanning from theoretical concepts to applied research, and featuring rigorous mathematical presentations on one side, as well as simplified explanations of many complex issues, on the other side, this book provides graduate students and researchers with a comprehensive introduction on the state of the art and a source of inspiration for future research. Moreover, the proposed concepts and methods can be extended to the simulation of multiphysical phenomena in different application contexts.
​This book serves as a single-source reference to key machine learning (ML) applications and methods in digital and analog design and verification. Experts from academia and industry cover a wide range of the latest research on ML applications in electronic design automation (EDA), including analysis and optimization of digital design, analysis and optimization of analog design, as well as functional verification, FPGA and system level designs, design for manufacturing (DFM), and design space exploration. The authors also cover key ML methods such as classical ML, deep learning models such as convolutional neural networks (CNNs), graph neural networks (GNNs), generative adversarial networks (GANs) and optimization methods such as reinforcement learning (RL) and Bayesian optimization (BO). All of these topics are valuable to chip designers and EDA developers and researchers working in digital and analog designs and verification.