Using Artificial Neural Networks for Analog Integrated Circuit Design Automation

Language: English

Published by Birkhäuser, 2020

3030357422 / 9783030357429

Series: Book 76 of 104 - SpringerBriefs in Continuum Mechanics

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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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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Title
Using Artificial Neural Networks for Analog Integrated Circuit Design Automation
Author
Daniel J. D. Guerra
Publisher
Birkhäuser
Publication year
2020
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
3030357422
ISBN 13
9783030357429
Item weight
195 grams
Dimensions
235x155x7 mm
Series
Book 76 of 104: SpringerBriefs in Continuum Mechanics

AHA-BUCH GmbH

Einbeck, Germany

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