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Geometry of linear matrix inequalities = a course in convexity and real algebraic geometry with a view towards optimization /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Geometry of linear matrix inequalities/ by Tim Netzer, Daniel Plaumann.
Reminder of title:	a course in convexity and real algebraic geometry with a view towards optimization /
Author:	Netzer, Tim.
other author:	Plaumann, Daniel.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	viii, 161 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Matrix inequalities. -
Online resource:	https://doi.org/10.1007/978-3-031-26455-9
ISBN:	9783031264559

Geometry of linear matrix inequalities = a course in convexity and real algebraic geometry with a view towards optimization /
Netzer, Tim.

Geometry of linear matrix inequalitiesa course in convexity and real algebraic geometry with a view towards optimization /[electronic resource] :by Tim Netzer, Daniel Plaumann. - Cham :Springer International Publishing :2023. - viii, 161 p. :ill., digital ;24 cm. - Compact textbooks in mathematics,2296-455X. - Compact textbooks in mathematics..

This textbook provides a thorough introduction to spectrahedra, which are the solution sets to linear matrix inequalities, emerging in convex and polynomial optimization, analysis, combinatorics, and algebraic geometry. Including a wealth of examples and exercises, this textbook guides the reader in helping to determine the convex sets that can be represented and approximated as spectrahedra and their shadows (projections) Several general results obtained in the last 15 years by a variety of different methods are presented in the book, along with the necessary background from algebra and geometry.

ISBN: 9783031264559

Standard No.: 10.1007/978-3-031-26455-9doiSubjects--Topical Terms:

528269
Matrix inequalities.

LC Class. No.: QA188 / .N48 2023

Dewey Class. No.: 512.9434

Geometry of linear matrix inequalities = a course in convexity and real algebraic geometry with a view towards optimization /
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