Pasricha sudeep (158 Ergebnisse)

hardcover. Zustand: Very Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or limited writing/highlighting. We ship orders daily and Customer Service is our top priority.

hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

Zustand: New. In English.

Gebundene Ausgabe. Zustand: Sehr gut. Gebraucht - Sehr gut sg - leichte beschädigungen oder verschmutzungen, ungelesenes mängelexemplar, gestempelt - Over the past decade, system-on-chip (SoC) designs have evolved to address the ever increasing complexity of applications, fueled by the era of digital convergence. Improvements in process technology have effectively shrunk board-level components so they can be integrated on a single chip. New on-chip communication architectures have been designed to support all inter-component communication in a SoC design. These communication architecture fabrics have a critical impact on the power consumption, performance, cost and design cycle time of modern SoC designs. As application complexity strains the communication backbone of SoC designs, academic and industrial R&D efforts and dollars are increasingly focused on communication architecture design. This book is a comprehensive reference on concepts, research and trends in on-chip communication architecture design. It will provide readers with a comprehensive survey, not available elsewhere, of all current standards for on-chip communication architectures. KEY FEATURES A definitive guide to on-chip communication architectures, explaining key concepts, surveying research efforts and predicting future trends Detailed analysis of all popular standards for on-chip communication architectures Comprehensive survey of all research on communication architectures, covering a wide range of topics relevant to this area, spanning the past several years, and up to date with the most current research efforts Future trends that with have a significant impact on research and design of communication architectures over the next several years.…

Paperback. Zustand: new. Paperback. While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve theaccuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book:Provides comprehensive coverage of the application of machine learning to the domain of indoor localization;Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization;Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Paperback. Zustand: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Zustand: New.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Zustand: New. 2023rd edition NO-PA16APR2015-KAP.

Paperback. Zustand: Brand New. 582 pages. 9.25x6.10x9.25 inches. In Stock.

Zustand: New.

hardcover. Zustand: Wie neu. 544 Seiten; 9780123738929.1 Gewicht in Gramm: 2.

Zustand: As New. Unread book in perfect condition.

Zustand: New.

Paperback / softback. Zustand: New. New copy - Usually dispatched within 4 working days.

Zustand: Wie Neu. Zustandsbeschreibung: leichte Lagerspuren, leicht bestoßen/minor shelfwear, slightly bumped. Edited by Vipin Kumar Kukkala and Sudeep Pasricha. With contributions by Wanli Chang, Nan Chen, Shuai Zhao, Xiaotian Dai et al. XV,789 Seiten, gebunden (Springer-Verlag 2023). Statt EUR 117,69. Gewicht: 137 g - Gebunden/Gebundene Ausgabe.…

Zustand: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Paperback. Zustand: Brand New. 540 pages. 9.25x7.50x1.22 inches. In Stock.

Zustand: New. In English.

Paperback. Zustand: New. 1st. Silicon photonics is beginning to play an important role in driving innovations in communication and computation for an increasing number of applications, from health care and biomedical sensors to autonomous driving, datacenter networking, and security. In recent years, there has been a significant amount of effort in industry and academia to innovate, design, develop, analyze, optimize, and fabricate systems employing silicon photonics, shaping the future of not only Datacom and telecom technology but also high-performance computing and emerging computing paradigms, such as optical computing and artificial intelligence. Different from existing books in this area, Silicon Photonics for High-Performance Computing and Beyond presents a comprehensive overview of the current state-of-the-art technology and research achievements in applying silicon photonics for communication and computation. It focuses on various design, development, and integration challenges, reviews the latest advances spanning materials, devices, circuits, systems, and applications. Technical topics discussed in the book include. Requirements and the latest advances in high-performance computing systems. Device- and system-level challenges and latest improvements to deploy silicon photonics in computing systems. Novel design solutions and design automation techniques for silicon photonic integrated circuits. Novel materials, devices, and photonic integrated circuits on silicon. Emerging computing technologies and applications based on silicon photonicsSilicon Photonics for High-Performance Computing and Beyond presents a compilation of 19 outstanding contributions from academic and industry pioneers in the field. The selected contributions present insightful discussions and innovative approaches to understand current and future bottlenecks in high-performance computing systems and traditional computing platforms, and the promise of silicon photonics to address those challenges. It is ideal for researchers and engineers working in the photonics, electrical, and computer engineering industries as well as academic researchers and graduate students (M.S. and Ph.D.) in computer science and engineering, electronic and electrical engineering, applied physics, photonics, and optics.…

Zustand: New.

Zustand: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Zustand: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Zustand: New.

Zustand: New.

Zustand: New.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve theaccuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation.In particular, the book:Provides comprehensive coverage of the application of machine learning to the domain of indoor localization;Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization;Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions.…