Machine Learning for Model Order Reduction

Authors: Mohamed, Khaled Salah

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  • Introduces machine learning algorithms at the architecture level and the algorithm levels of abstraction
  • Describes new, hybrid solutions for model order reduction
  • Presents machine learning algorithms in depth, but simply
  • Uses real, industrial applications to verify algorithms
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eBook 101,14 €
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  • ISBN 978-3-319-75714-8
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Hardcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-319-75713-1
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About this book

This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior.  The author describes techniques to reduce significantly the time required for simulations involving large-scale ordinary differential equations, which sometimes take several days or even weeks.  This method is called model order reduction (MOR), which reduces the complexity of the original large system and generates a reduced-order model (ROM) to represent the original one.  Readers will gain in-depth knowledge of machine learning and model order reduction concepts, the tradeoffs involved with using various algorithms, and how to apply the techniques presented to circuit simulations and numerical analysis.

  • Introduces machine learning algorithms at the architecture level and the algorithm levels of abstraction;
  • Describes new, hybrid solutions for model order reduction;
  • Presents machine learning algorithms in depth, but simply;
  • Uses real, industrial applications to verify algorithms.

About the authors

Khaled Salah Mohamed attended the school of engineering, Department of Electronics and Communications at Ain-Shams University from 1998 to 2003, where he received his B.Sc. degree in Electronics and Communications Engineering with distinction and honors. He received his Masters degree in Electronics from Cairo University, Egypt in 2008. He received his PhD degree in 2012. Dr. Khaled Salah is currently a Technical Lead at the Emulation division at Mentor Graphic, Egypt. Dr. Khaled Salah has published a large number of papers in in the top refereed journals and conferences. His research interests are in 3D integration, IP Modeling, and SoC design.

Table of contents (8 chapters)

  • Introduction

    Mohamed, Khaled Salah

    Pages 1-18

  • Bio-Inspired Machine Learning Algorithm: Genetic Algorithm

    Mohamed, Khaled Salah

    Pages 19-34

  • Thermo-Inspired Machine Learning Algorithm: Simulated Annealing

    Mohamed, Khaled Salah

    Pages 35-46

  • Nature-Inspired Machine Learning Algorithm: Particle Swarm Optimization, Artificial Bee Colony

    Mohamed, Khaled Salah

    Pages 47-56

  • Control-Inspired Machine Learning Algorithm: Fuzzy Logic Optimization

    Mohamed, Khaled Salah

    Pages 57-63

Buy this book

eBook 101,14 €
price for Spain (gross)
  • ISBN 978-3-319-75714-8
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 124,79 €
price for Spain (gross)
  • ISBN 978-3-319-75713-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning for Model Order Reduction
Authors
Copyright
2018
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-75714-8
DOI
10.1007/978-3-319-75714-8
Hardcover ISBN
978-3-319-75713-1
Edition Number
1
Number of Pages
XI, 93
Topics