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In-Memory Computing Hardware Accelerators for Data-Intensive Applications
This book describes the state-of-the-art of technology and research on In-Memory Computing Hardware Accelerators for Data-Intensive Applications. The authors discuss how processing-centric computing has become insufficient to meet target requirements and how Memory-centric computing may be better suited for the needs of current applications. This reveals for readers how current and emerging memory technologies are causing a shift in the computing paradigm. The authors do deep-dive discussions on volatile and non-volatile memory technologies, covering their basic memory cell structures, operations, different computational memory designs and the challenges associated with them. Specific case studies and potential applications are provided along with their current status and commercial availability in the market.
Artificial Intelligence for Medicine
Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and tailored clinical treatment are being quickly transformed by artificial intelligence (AI) and machine learning (ML). The content in this book is tailored to the reader's needs in terms of both type and fundamentals. It covers the current ethical issues and potential developments in this field. Artificial Intelligence ...
Memristor Technology: Synthesis and Modeling for Sensing and Security Applications
This book provides readers with a single-source guide to fabricate, characterize and model memristor devices for sensing applications. The authors describe a correlated, physics-based model to simulate and predict the behavior of devices fabricated with different oxide materials, active layer thickness, and operating temperature. They discuss memristors from various perspectives, including working mechanisms, different synthesis methods, characterization procedures, and device employment in radiation sensing and security applications.
Embedded Memory Design for Multi-Core and Systems on Chip
This book describes the various tradeoffs systems designers face when designing embedded memory. Readers designing multi-core systems and systems on chip will benefit from the discussion of different topics from memory architecture, array organization, circuit design techniques and design for test. The presentation enables a multi-disciplinary approach to chip design, which bridges the gap between the architecture level and circuit level, in order to address yield, reliability and power-related issues for embedded memory.
Digital Phase Lock Loops
This exciting new book covers various types of digital phase lock loops. It presents a comprehensive coverage of a new class of digital phase lock loops called the time delay tanlock loop (TDTL). It also details a number of architectures that improve the performance of the TDTL through adaptive techniques that overcome the conflicting requirements of the locking rage and speed of acquisition.
Intelligent Computing Applications for COVID-19
Accurate estimation, diagnosis, and prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI, and Mathematical Modeling applications. This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry. This book covers the state-of-the-art applications of AI and Machine Learning in past epidemics, pandemics, and COVID-19. It offers recent global case studies, and discusses how AI and statistical methods, initiatives, and applications such as Machine Learning, Deep Learning, Correlation and Regression Analysis play a major role in the prediction, diagnosis, and prevention of a pandemic. It will also focus on how AI and statistical applications can facilitate and restructure the healthcare system. This book is written for Researchers, Students, Professionals, Executives, and the general public.
In-Memory Computing Hardware Accelerators for Data-Intensive Applications
This book describes the state-of-the-art of technology and research on In-Memory Computing Hardware Accelerators for Data-Intensive Applications. The authors discuss how processing-centric computing has become insufficient to meet target requirements and how Memory-centric computing may be better suited for the needs of current applications. This reveals for readers how current and emerging memory technologies are causing a shift in the computing paradigm. The authors do deep-dive discussions on volatile and non-volatile memory technologies, covering their basic memory cell structures, operations, different computational memory designs and the challenges associated with them. Specific case studies and potential applications are provided along with their current status and commercial availability in the market. Explains how traditional computer architecture limits data movements (memory wall) and the associated impacts; Discusses computing paradigms such as In-Memory or near-memory computing for emerging applications such as AI; Uses case studies to explain the tradeoff between accuracy, computing complexity, and latency.
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