Hardcover. 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. Address vector and matrix methods necessary in numerical methods and optimization of linear systems with this practical, unified text. Perfect for advanced undergraduate students and graduate students in engineering, physical sciences, and applied mathematics. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Bestandsnummer des Verk�ufers 9781108479097

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Bibliografische Details

Titel: Matrix, Numerical, and Optimization Methods in Science and Engineering (Hardcover)
Verlag: Cambridge University Press, Cambridge
Erscheinungsjahr: 2021
Sprache: Englisch
ISBN-10: 110847909X
ISBN-13: 9781108479097
Einband: Hardcover
Zustand: new

�ber diesen Titel

Inhaltsangabe

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.

�ber die Autorin bzw. den Autor

Kevin W. Cassel is Professor of Mechanical and Aerospace Engineering and Professor of Applied Mathematics at the Illinois Institute of Technology. He is also an Associate Fellow of the American Institute of Aeronautics and Astronautics.

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