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{ "item_title" : "Matrix, Numerical, and Optimization Methods in Science and Engineering", "item_author" : [" Kevin W. Cassel "], "item_description" : "Address vector and matrix methods necessary in numerical methods and optimization of linear systems in engineering with this unified text. Treats the mathematical models that describe and predict the evolution of our processes and systems, and the numerical methods required to obtain approximate solutions. Explores the dynamical systems theory used to describe and characterize system behaviour, alongside the techniques used to optimize their performance. Integrates and unifies matrix and eigenfunction methods with their applications in numerical and optimization methods. Consolidating, generalizing, and unifying these topics into a single coherent subject, this practical resource is suitable for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/10/847/909/110847909X_b.jpg", "price_data" : { "retail_price" : "135.00", "online_price" : "135.00", "our_price" : "135.00", "club_price" : "135.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Matrix, Numerical, and Optimization Methods in Science and Engineering|Kevin W. Cassel

Matrix, Numerical, and Optimization Methods in Science and Engineering

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Overview

Address vector and matrix methods necessary in numerical methods and optimization of linear systems in engineering with this unified text. Treats the mathematical models that describe and predict the evolution of our processes and systems, and the numerical methods required to obtain approximate solutions. Explores the dynamical systems theory used to describe and characterize system behaviour, alongside the techniques used to optimize their performance. Integrates and unifies matrix and eigenfunction methods with their applications in numerical and optimization methods. Consolidating, generalizing, and unifying these topics into a single coherent subject, this practical resource is suitable for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics.

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Details

  • ISBN-13: 9781108479097
  • ISBN-10: 110847909X
  • Publisher: Cambridge University Press
  • Publish Date: March 2021
  • Dimensions: 9.61 x 6.69 x 1.56 inches
  • Shipping Weight: 2.97 pounds
  • Page Count: 728

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