Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Machine Learning For Model Order ReductionISBN13:9783319757131ISBN10:331975713XAuthor:Mohamed, Khaled Salah (Author)Description: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 Binding:Hardcover, HardcoverPublisher:SPRINGER NATUREPublication Date:2018-03-09Weight:0.73 lbsDimensions:0.31'' H x 9.21'' L x 6.14'' WNumber of Pages:93Language:English
Price: 122.9 USD
Location: USA
End Time: 2024-09-05T01:23:54.000Z
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Book Title: Machine Learning for Model Order Reduction
Item Length: 9.3in
Item Width: 6.1in
Author: Khaled Salah Mohamed
Format: Hardcover
Language: English
Topic: Systems Architecture / General, Electronics / Circuits / Vlsi & Ulsi, Electronics / Circuits / General, Electronics / General
Publisher: Springer International Publishing A&G
Publication Year: 2018
Genre: Technology & Engineering, Computers
Item Weight: 16 Oz
Number of Pages: Xi, 93 Pages