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Using Artificial Neural Networks by Rosa João (18 results)
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Condition: As New. Unread book in perfect condition.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation (SpringerBriefs in Applied Sciences and Technology)
Book 76 of 104: SpringerBriefs in Continuum MechanicsSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 74.70
US$ 15.69 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Book 76 of 104: SpringerBriefs in Continuum MechanicsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Book 76 of 104: SpringerBriefs in Continuum MechanicsPublished by Springer Nature Switzerland AG, CH, 2020
ISBN 10: 3030357422 ISBN 13: 9783030357429
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: New. 2020 ed.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Book 76 of 104: SpringerBriefs in Continuum MechanicsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Paperback. Condition: Brand New. 120 pages. 9.25x6.10x0.28 inches. In Stock.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Book 76 of 104: SpringerBriefs in Continuum MechanicsPublished by Springer International Publishing, Springer Nature Switzerland Jan 2020, 2020
ISBN 10: 3030357422 ISBN 13: 9783030357429
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices¿ sizes to circuits¿ performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices¿ sizes. Two separate ANN architectures are proposed: a Regression-only model and a Classification and Regression model. The goal of the Regression-only model is to learn design patterns from the studied circuits, using circuit¿s performances as input features and devices¿ sizes as target outputs. This model can size a circuit given its specifications for a single topology. The Classification and Regression model has the same capabilities of the previous model, but it can also select the most appropriate circuit topology and its respective sizing given the target specification. The proposed methodology was implemented and tested on two analog circuit topologies.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 120 pp. Englisch.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Book 76 of 104: SpringerBriefs in Continuum MechanicsPublished by Springer International Publishing, Springer Nature Switzerland, 2020
ISBN 10: 3030357422 ISBN 13: 9783030357429
Language: English
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices' sizes to circuits' performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices' sizes. Two separate ANN architectures are proposed: a Regression-only model and a Classification and Regression model. The goal of the Regression-only model is to learn design patterns from the studied circuits, using circuit's performances as input features and devices' sizes as target outputs. This model can size a circuit given its specifications for a single topology. The Classification and Regression model has the same capabilities of the previous model, but it can also select the most appropriate circuit topology and its respective sizing given the target specification. The proposed methodology was implemented and tested on two analog circuit topologies.
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Taschenbuch. Condition: Neu. Using Artificial Neural Networks for Analog Integrated Circuit Design Automation | João P. S. Rosa (u. a.) | Taschenbuch | xviii | Englisch | 2020 | Springer | EAN 9783030357429 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Book 76 of 104: SpringerBriefs in Continuum MechanicsPublished by Springer Nature Switzerland AG, CH, 2020
ISBN 10: 3030357422 ISBN 13: 9783030357429
Language: English
Paperback. Condition: New. 2020 ed.
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Paperback. Condition: Brand New. 120 pages. 9.25x6.10x0.28 inches. In Stock. This item is printed on demand.
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Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Book 76 of 104: SpringerBriefs in Continuum MechanicsPublished by Springer International Publishing, Springer International Publishing Jan 2020, 2020
ISBN 10: 3030357422 ISBN 13: 9783030357429
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book addresses the automatic sizing and layout of analog integrated circuits (ICs) using deep learning (DL) and artificial neural networks (ANN). It explores an innovative approach to automatic circuit sizing where ANNs learn patterns from previously optimized design solutions. In opposition to classical optimization-based sizing strategies, where computational intelligence techniques are used to iterate over the map from devices' sizes to circuits' performances provided by design equations or circuit simulations, ANNs are shown to be capable of solving analog IC sizing as a direct map from specifications to the devices' sizes. Two separate ANN architectures are proposed: a Regression-only model and a Classification and Regression model. The goal of the Regression-only model is to learn design patterns from the studied circuits, using circuit's performances as input features and devices' sizes as target outputs. This model can size a circuit given its specifications for a single topology. The Classification and Regression model has the same capabilities of the previous model, but it can also select the most appropriate circuit topology and its respective sizing given the target specification. The proposed methodology was implemented and tested on two analog circuit topologies. 120 pp. Englisch.
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