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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List of Symbols, Notations and Abbreviations. Preface. 1. Analog Parallel Signal Processing. 2. Implications of Mismatch on Analog VLSI. 3. Implementation Oriented Theory for CNN's. 4. VLSI Implementation of CNN's. 5. General Conclusions. Appendices. A-MOS Transistor Models. Bibliography. Index.
Book by Kinget Peter Steyaert Michiel
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Hardcover. Condizione: new. Hardcover. When comparing conventional computing architectures to the architectures of biological neural systems, there are 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 different computing paradigm: a massive network of simple processors that are (adaptively) interconnected and operate in parallel. This massively parallel processing seems the key aspect to their success. The advent of VLSI technologies has provided us with the technological means to implement very complicated systems on a silicon die. Analog VLSI circuits in standard digital technologies open the way for the implementation of massively parallel analog signal processing systems for sensory signal processing applications and for perception tasks.This text describes in depth the theory and practice of designing these 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. 4 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9780792398233
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Buch. Condizione: 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 GmbH, Tiergartenstr. 17, 69121 Heidelberg 248 pp. Englisch. Codice articolo 9780792398233
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