Geometry of Linear Matrix Inequalities: A Course in Convexity and Real Algebraic Geometry with a View Towards Optimization
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...
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creator | Netzer, Tim Plaumann, Daniel |
description | 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. |
doi_str_mv | 10.1007/978-3-031-26455-9 |
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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). 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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.</description><subject>Algebraic Geometry</subject><subject>Convex and Discrete Geometry</subject><subject>Convex domains</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Matrix inequalities</subject><subject>Optimization</subject><issn>2296-4568</issn><issn>2296-455X</issn><isbn>9783031264542</isbn><isbn>3031264541</isbn><isbn>303126455X</isbn><isbn>9783031264559</isbn><fulltext>true</fulltext><rsrctype>book</rsrctype><creationdate>2023</creationdate><recordtype>book</recordtype><sourceid/><recordid>eNpNkEtPwzAQhM1TtKU_gFtOIA6m62fsI0SlVCrighA3y0kcCA1JG6dQ_j1JA4jT7mi-GWkXoTMCVwQgnOhQYYaBEUwlFwLrPTRkrdyp5300oFRL3O0HaNzCvx6nh3-eVMdoSJiiUreCn6Cx928AQJWSINgAnc9c9e6a-iuosmCRl87Wwb1t6nwbzEu33tgib3LnT9FRZgvvxj9zhJ5up4_RHV48zObR9QJbQhjfYm0tTy1VwkIsnIhppmMmBIE4zBhNSBZnQoIKFQ-tDDUknNNUJMylkErLORuhy77Y-qX79K9V0XjzUbi4qpbe_LtS6Jad9Kxf1Xn54mrTUwRM98CONsy0vNkFTJe46BOrulpvnG_MrjhxZVPbwkxvopBK4JKzb6nZZwM</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Netzer, Tim</creator><creator>Plaumann, Daniel</creator><general>Springer International Publishing AG</general><general>Springer International Publishing</general><scope/></search><sort><creationdate>2023</creationdate><title>Geometry of Linear Matrix Inequalities</title><author>Netzer, Tim ; Plaumann, Daniel</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a1134x-9aa4da285a0b5e5b2f9b35510b7f32c1fbf56087847a6790c442d5c3ed0d6a443</frbrgroupid><rsrctype>books</rsrctype><prefilter>books</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algebraic Geometry</topic><topic>Convex and Discrete Geometry</topic><topic>Convex domains</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Matrix inequalities</topic><topic>Optimization</topic><toplevel>online_resources</toplevel><creatorcontrib>Netzer, Tim</creatorcontrib><creatorcontrib>Plaumann, Daniel</creatorcontrib></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Netzer, Tim</au><au>Plaumann, Daniel</au><format>book</format><genre>book</genre><ristype>BOOK</ristype><btitle>Geometry of Linear Matrix Inequalities: A Course in Convexity and Real Algebraic Geometry with a View Towards Optimization</btitle><seriestitle>Compact Textbooks in Mathematics</seriestitle><date>2023</date><risdate>2023</risdate><issn>2296-4568</issn><eissn>2296-455X</eissn><isbn>9783031264542</isbn><isbn>3031264541</isbn><eisbn>303126455X</eisbn><eisbn>9783031264559</eisbn><abstract>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. 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subjects | Algebraic Geometry Convex and Discrete Geometry Convex domains Mathematics Mathematics and Statistics Matrix inequalities Optimization |
title | Geometry of Linear Matrix Inequalities: A Course in Convexity and Real Algebraic Geometry with a View Towards Optimization |
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