Atjaunināt sīkdatņu piekrišanu

E-grāmata: Machine Learning for Model Order Reduction

1.00/5 (2 ratings by Goodreads)
  • Formāts: EPUB+DRM
  • Izdošanas datums: 02-Mar-2018
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319757148
Citas grāmatas par šo tēmu:
  • Formāts - EPUB+DRM
  • Cena: 130,27 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
Machine Learning for Model Order ReductionPalielināt
  • Formāts: EPUB+DRM
  • Izdošanas datums: 02-Mar-2018
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319757148
Citas grāmatas par šo tēmu:

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

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.

Chapter1: Introduction.
Chapter2: Bio-Inspired Machine Learning Algorithm: Genetic Algorithm.
Chapter3: Thermo-Inspired Machine Learning Algorithm: Simulated Annealing.
Chapter4: Nature-Inspired Machine Learning Algorithm: Particle Swarm Optimization, Artificial Bee Colony.
Chapter5: Control-Inspired Machine Learning Algorithm: Fuzzy Logic Optimization.
Chapter6: Brain-Inspired Machine Learning Algorithm: Neural Network Optimization.
Chapter7: Comparisons, Hybrid Solutions, Hardware architectures and New Directions.
Chapter8: Conclusions.

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.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
Permanent link: https://www.kriso.lv/db/97833197571486e.html
Keywords: