Smart Adaptive Systems on Silicon

Maurizio Valle

ISBN 10: 1402027435 / ISBN 13: 9781402027437

Editore: Springer US, Springer US Okt 2004, 2004

Riguardo questo articolo

Neuware -Intelligent/smart systems have become common practice in many engineering applications. On the other hand, current low cost standard CMOS technology (and future foreseeable developments) makes available enormous potentialities. The next breakthrough will be the design and development of 'smart adaptive systems on silicon' i.e. very power and highly size efficient complete systems (i.e. sensing, computing and 'actuating' actions) with intelligence on board on a single silicon die. Smart adaptive systems on silicon will be able to 'adapt' autonomously to the changing environment and will be able to implement 'intelligent' behaviour and both perceptual and cognitive tasks. At last, they will communicate through wireless channels, they will be battery supplied or remote powered (via inductive coupling) and they will be ubiquitous in our every day life.Although many books deal with research and engineering topics (i.e. algorithms, technology, implementations, etc.) few of them try to bridge the gap between them and to address the issues related to feasibility, reliability and applications. Smart Adaptive Systems on Silicon, though not exhaustive, tries to fill this gap and to give answers mainly to the feasibility and reliability issues.Smart Adaptive Systems on Silicon mainly focuses on the analog and mixed mode implementation on silicon because this approach is amenable of achieving impressive energy and size efficiency. Moreover, analog systems can be more easily interfaced with sensing and actuating devices.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 320 pp. Englisch.

Codice articolo 9781402027437

Dati bibliografici

• Titolo: Smart Adaptive Systems on Silicon
• Editore: Springer US, Springer US Okt 2004
• Data di pubblicazione: 2004
• Lingua: Inglese
• ISBN 10: 1402027435
• ISBN 13: 9781402027437
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 22 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 22 millimetri di profondità
• Peso: 647 grammi

Descrizione articolo

Riassunto

Intelligent/smart systems have become common practice in many engineering applications. On the other hand, current low cost standard CMOS technology (and future foreseeable developments) makes available enormous potentialities. The next breakthrough will be the design and development of "smart adaptive systems on silicon" i.e. very power and highly size efficient complete systems (i.e. sensing, computing and "actuating" actions) with intelligence on board on a single silicon die. Smart adaptive systems on silicon will be able to "adapt" autonomously to the changing environment and will be able to implement "intelligent" behaviour and both perceptual and cognitive tasks. At last, they will communicate through wireless channels, they will be battery supplied or remote powered (via inductive coupling) and they will be ubiquitous in our every day life.

Although many books deal with research and engineering topics (i.e. algorithms, technology, implementations, etc.) few of them try to bridge the gap between them and to address the issues related to feasibility, reliability and applications. Smart Adaptive Systems on Silicon, though not exhaustive, tries to fill this gap and to give answers mainly to the feasibility and reliability issues.

Smart Adaptive Systems on Silicon mainly focuses on the analog and mixed mode implementation on silicon because this approach is amenable of achieving impressive energy and size efficiency. Moreover, analog systems can be more easily interfaced with sensing and actuating devices.

Contenuti

Dedication. Preface. Part I: Silicon Technology. 1. The CMOS Technology Platform. 2. Systems On A Chip. 3. Microsystems. 4. Soi Technology. Part II: Perception Systems On Silicon. 5. Neuromorphic Engineering. 6. Vertebrate Retina Emulation Using Multi-Layer Array-Processor Mixed-Signal Chips. 7. CMOS Mixed-Signal Flexible Vision Chips. 8. How To Organize Analog VLSI Operators To Perform Perceptual Tasks In Machine Vision. Part III: Cognitive Systems On Silicon. 9. Supervised Learning Systems On Silicon. 10. Design And Application Of Analog Fuzzy Logic Controllers. 11. Unsupervised Probabilistic Neural Computation In Analogue VLSI. 12. Evolvable Hardware In Silicon. 13. Mixed-Mode Neural Networks Adapted For Evolutionary Algorithms. Part IV: Systems On Silicon. 14. Log-Domain Circuit Techniques For Nonlinear Neural Networks With Complex Dynamics. 15. Remote Powering And Control Of Intelligent Microsystems. 16. Nonuniformity Correction Of Imaging Arrays Using The Constant Statistics Constraint. 17. Bioartificial Neuronal Networks: Coupling Networks Of Biological Neuron To Microtransducer Arrays. Index.