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 (adaptively) interconnected and operate in parallel. Exactly this massively parallel processing seems the key aspect to their success. On the other hand the development of VLSI technologies provide us with technological means to implement very complicated systems on a silicon die. Especially analog VLSI circuits in standard digital technologies open the way for the implement at ion of massively parallel analog signal processing systems for sensory signal processing applications and for perception tasks. In chapter 1 the motivations behind the emergence of the analog VLSI of massively parallel systems is discussed in detail together with the capabilities and !imitations of VLSI technologies and the required research and developments. Analog parallel signal processing drives for the development of very com pact, high speed and low power circuits. An important technologicallimitation in the reduction of the size of circuits and the improvement of the speed and power consumption performance is the device inaccuracies or device mismatch.
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Trent McConaghy is co-founder and Chief Scientific Officer of Solido Design Automation Inc. He was a co-founder and Chief Scientist of Analog Design Automation Inc., which was acquired by Synopsys Inc. in 2004. Prior to that, he did research for the Canadian Department of National Defense. He received his PhD degree in Electrical Engineering from the Katholieke Universiteit Leuven, Belgium, in 2008. He received a Bachelor's in Engineering (with great distinction), and a Bachelor's in Computer Science (with great distinction), both from the University of Saskatchewan, Canada, in 1999. He has about 40 peer-reviewed technical papers and patents granted / pending. He has given invited talks / tutorials at many labs, universities, and conferences such as JPL, MIT, ICCAD, and DAC. He is regularly a technical program committee member and reviewer in both the CAD and intelligent systems fields, such as IEEE Trans CAD, ACM TODAES, Electronics Letters, to IEEE Trans Evolutionary Computation, the Journal of Genetic Programming and Evolvable Machines, GPTP, GECCO, ICES, etc. His research interest is in statistical machine learning and intelligent systems, with transistor-level CAD applications such as variation-aware design, analog topology design, automated sizing, knowledge extraction, and symbolic modeling.Michiel Steyaert was born in Aalst, Belgium, in 1959. He received the masters degree in electrical-mechanical engineering and the Ph.D. degree in electronics from the Katholieke Universiteit Leuven (K.U.Leuven), Heverlee, Belgium in 1983 and 1987, respectively. From 1983 to 1986 he obtained an IWNOL fellowship (Belgian National Fundation for Industrial Research) which allowed him to work as a Research Assistant at the Laboratory ESAT at K.U.Leuven. In 1987 he was responsible for several industrial projects in the field of analog micropower circuits at the Laboratory ESAT as an IWONL Project Researcher. In 1988 he was a Visiting Assistant Professor atthe University of California, Los Angeles. In 1989 he was appointed by the National Fund of Scientific Research (Belgium) as Research Associate, in 1992 as a Senior Research Associate and in 1996 as a Research Director at the Laboratory ESAT, K.U.Leuven. Between 1989 and 1996 he was also a part-time Associate Professor. He is now a Full Professor at the K.U.Leuven. His current research interests are in high-performance and high-frequency analog integrated circuits for telecommunication systems and analog signal processing. Prof.Steyaert received the 1990 and 2001 European Solid-State Circuits Conference Best Paper Award. He received the 1991 and the 2000 NFWO Alcatel-Bell-Telephone award for innovative work in integrated circuits for telecommunications. Prof.Steyaert received the 1995 and 1997 IEEE-ISSCC Evening Session Award, the 1999 IEEE Circuit and Systems Society Guillemin-Cauer Award and is currently an IEEE-Fellow.Georges Gielen received the MSc and PhD degrees in Electrical Engineering from the Katholieke Universiteit Leuven, Belgium, in 1986 and 1990, respectively. He currently is a Full Professor at the Katholieke Universiteit Leuven. His research interests are in the design of analog and mixed-signal integrated circuits, and especially in analog and mixed-signal CAD tools and design automation (modeling, simulation and symbolic analysis, analog synthesis, analog layout generation, analog and mixed-signal testing). He is coordinator or partner of several (industrial) research projects in this area, including several European projects (EU, MEDEA, ESA). He has authored or coauthored five books and more than 300 papers in edited books, international journals and conference proceedings. He regularly is a member of the Program Committees of international conferences (DAC, ICCAD, ISCAS, DATE, CICC...), and served as General Chair of the DATE conference in 2006 and of the International Conference on Computer-Aided Design in 2007. He serves regularly as member of editorial boards of
Analog VLSI Integration of Massive Parallel Processing Systems describes in depth the theory and practice of designing massively parallel analog signal processing systems. Techniques are described which overcome the device and transistor mismatches which limit performance of the system. The book also shows how such a system can be efficiently implemented using cellular Neural Networks. Analog VLSI Integration of Massive Parallel Processing Systems is essential reading for practicing analog design engineers and researchers in the field. It is also suitable as a text for an advanced course on the subject.
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Zustand: New. This text describes in depth the theory and practice of designing massively parallel analog signal processing systems. Techniques are described which overcome the device and transistor mismatches which limit performance of the system. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 241 pages, biography. BIC Classification: TJF; UY. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 15. Weight in Grams: 526. . 1996. Hardback. . . . . Bestandsnummer des Verkäufers V9780792398233
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 (adaptively) interconnected and operate in parallel. Exactly this massively parallel processing seems the key aspect to their success. On the other hand the development of VLSI technologies provide us with technological means to implement very complicated systems on a silicon die. Especially analog VLSI circuits in standard digital technologies open the way for the implement at ion of massively parallel analog signal processing systems for sensory signal processing applications and for perception tasks. In chapter 1 the motivations behind the emergence of the analog VLSI of massively parallel systems is discussed in detail together with the capabilities and !imitations of VLSI technologies and the required research and developments. Analog parallel signal processing drives for the development of very com pact, high speed and low power circuits. An important technologicallimitation in the reduction of the size of circuits and the improvement of the speed and power consumption performance is the device inaccuracies or device mismatch. Bestandsnummer des Verkäufers 9780792398233
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Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 (adaptively) interconnected and operate in parallel. Exactly this massively parallel processing seems the key aspect to their success. On the other hand the development of VLSI technologies provide us with technological means to implement very complicated systems on a silicon die. Especially analog VLSI circuits in standard digital technologies open the way for the implement at ion of massively parallel analog signal processing systems for sensory signal processing applications and for perception tasks. In chapter 1 the motivations behind the emergence of the analog VLSI of massively parallel systems is discussed in detail together with the capabilities and !imitations of VLSI technologies and the required research and developments. Analog parallel signal processing drives for the development of very com pact, high speed and low power circuits. An important technologicallimitation in the reduction of the size of circuits and the improvement of the speed and power consumption performance is the device inaccuracies or device mismatch.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 248 pp. Englisch. Bestandsnummer des Verkäufers 9780792398233
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Zustand: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | 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 (adaptively) interconnected and operate in parallel. Exactly this massively parallel processing seems the key aspect to their success. On the other hand the development of VLSI technologies provide us with technological means to implement very complicated systems on a silicon die. Especially analog VLSI circuits in standard digital technologies open the way for the implement at ion of massively parallel analog signal processing systems for sensory signal processing applications and for perception tasks. In chapter 1 the motivations behind the emergence of the analog VLSI of massively parallel systems is discussed in detail together with the capabilities and !imitations of VLSI technologies and the required research and developments. Analog parallel signal processing drives for the development of very com pact, high speed and low power circuits. An important technologicallimitation in the reduction of the size of circuits and the improvement of the speed and power consumption performance is the device inaccuracies or device mismatch. Bestandsnummer des Verkäufers 3022700/3
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