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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
EUR 12,32 per la spedizione da U.S.A. a Italia
Destinazione, tempi e costiEUR 8,05 per la spedizione da Regno Unito a Italia
Destinazione, tempi e costiDa: Books From California, Simi Valley, CA, U.S.A.
paperback. Condizione: Good. Minimal markings from previous owner threwout pages. Codice articolo mon0003806158
Quantitą: 1 disponibili
Da: Speedyhen, London, Regno Unito
Condizione: NEW. Codice articolo NW9783030357429
Quantitą: 1 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9783030357429_new
Quantitą: Pił di 20 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: New. Codice articolo 39636480-n
Quantitą: 1 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: 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. Codice articolo 9783030357429
Quantitą: 2 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 39636480
Quantitą: 1 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: 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. Codice articolo 9783030357429
Quantitą: 1 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: 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 devicesæ sizes to circuitsæ 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 devicesæ 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 circuitæs performances as input features and devicesæ 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. Codice articolo 9783030357429
Quantitą: 2 disponibili
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Condizione: As New. Unread book in perfect condition. Codice articolo 39636480
Quantitą: 1 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 39636480-n
Quantitą: 1 disponibili