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From its earliest days under English rule, New York City had an unusually diverse ethnic makeup, with substantial numbers of Dutch, English, Scottish, Irish, French, German, and Jewish immigrants, as well as a large African-American population. Joyce Goodfriend paints a vivid portrait of this society, exploring the meaning of ethnicity in early America and showing how colonial settlers of varying backgrounds worked out a basis for coexistence. She argues that, contrary to the prevalent notion of rapid Anglicization, ethnicity proved an enduring force in this small urban society well into the eighteenth century.
Solid-State Imaging with Charge-Coupled Devices covers the complete imaging chain: from the CCD's fundamentals to the applications. The book is divided into four main parts: the first deals with the basics of the charge-coupled devices in general. The second explains the imaging concepts in close relation to the classical television application. Part three goes into detail on new developments in the solid-state imaging world (light sensitivity, noise, device architectures), and part four rounds off the discussion with a variety of applications and the imager technology. The book is a reference work intended for all who deal with one or more aspects of solid- state imaging: the educational, scientific and industrial world. Graduates, undergraduates, engineers and technicians interested in the physics of solid-state imagers will find the answers to their imaging questions. Since each chapter concludes with a short section `Worth Memorizing', reading this short summary allows readers to continue their reading without missing the main message from the previous section.
Although it is now possible to integrate many millions of transistors on a single chip, traditional digital circuit technology is now reaching its limits, facing problems of cost and technical efficiency when scaled down to ever-smaller feature sizes. The analysis of biological neural systems, especially for visual processing, has allowed engineers to better understand how complex networks can effectively process large amounts of information, whilst dealing with difficult computational challenges. Analog and parallel processing are key characteristics of biological neural networks. Analog VLSI circuits using the same features can therefore be developed to emulate brain-style processing. Usin...
This history of computing focuses not on chronology (what came first and who deserves credit for it) but on the actual architectures of the first machines that made electronic computing a practical reality. The book covers computers built in the United States, Germany, England, and Japan. It makes clear that similar concepts were often pursued simultaneously and that the early researchers explored many architectures beyond the von Neumann architecture that eventually became canonical. The contributors include not only historians but also engineers and computer pioneers. An introductory chapter describes the elements of computer architecture and explains why "being first" is even less interes...
Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. Neural Information Processing and VLSI systematically presents various neural network paradigms, computing architectures, and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and audito...
This book brings together in one place important contributions and state-of-the-art research in the rapidly advancing area of analog VLSI neural networks. The book serves as an excellent reference, providing insights into some of the most important issues in analog VLSI neural networks research efforts.
This work explores the conception, design, construction, use, and afterlife of ENIAC, the first general purpose digital electronic computer.
When comparing conventional computing architectures to the architectures of biological neural systems, we find several striking differences. Conventional computers use a low number of high performance computing elements that are programmed with algorithms to perform tasks in a time sequenced way; they are very successful in administrative applications, in scientific simulations, and in certain signal processing applications. However, the biological systems still significantly outperform conventional computers in perception tasks, sensory data processing and motory control. Biological systems use a completely dif ferent computing paradigm: a massive network of simple processors that are (adap...