Analog VLSI Integration of Massive Parallel Signal Processing Systems:
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; th...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1997
|
| Schriftenreihe: | The Springer International Series in Engineering and Computer Science
384 |
| Schlagworte: | |
| Online-Zugang: | BTU01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XIII, 228 p) |
| ISBN: | 9781475725803 |
| DOI: | 10.1007/978-1-4757-2580-3 |
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| 520 | |a 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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| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
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| id | DE-604.BV045187069 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:10:58Z |
| institution | BVB |
| isbn | 9781475725803 |
| language | English |
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| publishDate | 1997 |
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| series2 | The Springer International Series in Engineering and Computer Science |
| spelling | Kinget, Peter Verfasser aut Analog VLSI Integration of Massive Parallel Signal Processing Systems by Peter Kinget, Michiel Steyaert Boston, MA Springer US 1997 1 Online-Ressource (XIII, 228 p) txt rdacontent c rdamedia cr rdacarrier The Springer International Series in Engineering and Computer Science 384 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 Engineering Electrical Engineering Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Statistical physics Dynamical systems Electrical engineering Steyaert, Michiel aut Erscheint auch als Druck-Ausgabe 9781441951687 https://doi.org/10.1007/978-1-4757-2580-3 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Kinget, Peter Steyaert, Michiel Analog VLSI Integration of Massive Parallel Signal Processing Systems Engineering Electrical Engineering Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Statistical physics Dynamical systems Electrical engineering |
| title | Analog VLSI Integration of Massive Parallel Signal Processing Systems |
| title_auth | Analog VLSI Integration of Massive Parallel Signal Processing Systems |
| title_exact_search | Analog VLSI Integration of Massive Parallel Signal Processing Systems |
| title_full | Analog VLSI Integration of Massive Parallel Signal Processing Systems by Peter Kinget, Michiel Steyaert |
| title_fullStr | Analog VLSI Integration of Massive Parallel Signal Processing Systems by Peter Kinget, Michiel Steyaert |
| title_full_unstemmed | Analog VLSI Integration of Massive Parallel Signal Processing Systems by Peter Kinget, Michiel Steyaert |
| title_short | Analog VLSI Integration of Massive Parallel Signal Processing Systems |
| title_sort | analog vlsi integration of massive parallel signal processing systems |
| topic | Engineering Electrical Engineering Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Statistical physics Dynamical systems Electrical engineering |
| topic_facet | Engineering Electrical Engineering Statistical Physics, Dynamical Systems and Complexity Signal, Image and Speech Processing Statistical physics Dynamical systems Electrical engineering |
| url | https://doi.org/10.1007/978-1-4757-2580-3 |
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