Streamlined Design Solutions Specifically for NoC To solve critical network-on-chip (NoC) architecture and design problems related to structure, performance and modularity, engineers generally rely on guidance from the abundance of literature about better-understood system-level interconnection networks. However, on-chip networks present several distinct challenges that require novel and specialized solutions not found in the tried-and-true system-level techniques. A Balanced Analysis of NoC Architecture As the first detailed description of the commercial Spidergon STNoC architecture, Design of Cost-Efficient Interconnect Processing Units: Spidergon STNoC examines the highly regarded, cost-cutting technology that is set to replace well-known shared bus architectures, such as STBus, for demanding multiprocessor system-on-chip (SoC) applications. Employing a balanced, well-organized structure, simple teaching methods, numerous illustrations, and easy-to-understand examples, the authors explain: how the SoC and NoC technology works why developers designed it the way they did the system-level design methodology and tools used to configure the Spidergon STNoC architecture differences in cost structure between NoCs and system-level networks From professionals in computer sciences, electrical engineering, and other related fields, to semiconductor vendors and investors – all readers will appreciate the encyclopedic treatment of background NoC information ranging from CMPs to the basics of interconnection networks. The text introduces innovative system-level design methodology and tools for efficient design space exploration and topology selection. It also provides a wealth of key theoretical and practical MPSoC and NoC topics, such as technological deep sub-micron effects, homogeneous and heterogeneous processor architectures, multicore SoC, interconnect processing units, generic NoC components, and embeddings of common communication patterns.
This book offers a detailed history of plastic surgery procedures and their development from the ancient world, through the Middle Ages and the Renaissance, up to World War II. The origin of plastic surgery is essentially the story of wound management – the frequent struggle that primitive man engaged in to heal his injuries. The narrative chronicles the rise and fall – and rise again – of the discipline through the centuries. It illustrates the birth of modern reconstructive and aesthetic techniques and emphasizes the ingenuity that plastic surgeons demonstrated to improve wound defects and refine facial disfigurements of various origins, congenital or acquired. In addition, the work underscores the enormous impact that the study of human anatomy had on the evolution of surgery. Chapters discuss the birth and spread of aesthetic surgery, seldom referenced in modern scientific writing. Richly illustrated with hundreds of images drawn from the personal collection of the primary author, the book is an outstanding contribution to the annals of surgery. Not only does it honor the publications and artworks that have recorded these unique achievements, it also recognizes the great innovators of the past whose reconstructive and aesthetic work forms the basis of today’s surgical successes. Plastic Surgery – An Illustrated History is a must-have resource for plastic, maxillofacial and aesthetic surgeons. Any student of surgery, medical history, or medical illustration will be interested in this work.
Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc. Features of the text include: • a general functional optimization framework; • thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems; • comparison of classical and neural-network based methods of approximate solution; • bounds to the errors of approximate solutions; • solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several; • applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and • numerous, numerically detailed examples. The authors’ diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.
In the early 1980s, the late luminary Tito Arecchi was the first to highlight the existence of chaos in a laser model. Since then, along with several colleagues, he developed many important lines of research in this field, such as generalized multistability, laser with injected signal, laser with delayed feedback and the worldwide accepted classification of lasers of A, B and C, depending on their typical relaxation rates. Later, chaos control and synchronization were investigated in lasers and other systems, providing innovative schemes. Very recently, in his last contribution to laser physics, the model of the laser with feedback demonstrating its universal features was revisited.This book aims to present the research activity of Prof. Arecchi and his colleagues in the domain of nonlinear dynamics of lasers, since his seminal works of 1982 till the latest. Also included is our last contribution on jerk dynamics of laser's minimal universal model and a brief history of the discovery of laser where the reader will discover or rediscover many anecdotes about it.
Streamlined Design Solutions Specifically for NoC To solve critical network-on-chip (NoC) architecture and design problems related to structure, performance and modularity, engineers generally rely on guidance from the abundance of literature about better-understood system-level interconnection networks. However, on-chip networks present several distinct challenges that require novel and specialized solutions not found in the tried-and-true system-level techniques. A Balanced Analysis of NoC Architecture As the first detailed description of the commercial Spidergon STNoC architecture, Design of Cost-Efficient Interconnect Processing Units: Spidergon STNoC examines the highly regarded, cost-cutting technology that is set to replace well-known shared bus architectures, such as STBus, for demanding multiprocessor system-on-chip (SoC) applications. Employing a balanced, well-organized structure, simple teaching methods, numerous illustrations, and easy-to-understand examples, the authors explain: how the SoC and NoC technology works why developers designed it the way they did the system-level design methodology and tools used to configure the Spidergon STNoC architecture differences in cost structure between NoCs and system-level networks From professionals in computer sciences, electrical engineering, and other related fields, to semiconductor vendors and investors – all readers will appreciate the encyclopedic treatment of background NoC information ranging from CMPs to the basics of interconnection networks. The text introduces innovative system-level design methodology and tools for efficient design space exploration and topology selection. It also provides a wealth of key theoretical and practical MPSoC and NoC topics, such as technological deep sub-micron effects, homogeneous and heterogeneous processor architectures, multicore SoC, interconnect processing units, generic NoC components, and embeddings of common communication patterns.
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