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Record Nr. |
UNINA9910789997403321 |
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Autore |
Kosmol Peter |
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Titolo |
Optimization in function spaces [[electronic resource] ] : with stability considerations in Orlicz spaces / / Peter Kosmol, Dieter Müller-Wichards |
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Pubbl/distr/stampa |
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Berlin ; ; New York, : De Gruyter, 2011 |
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ISBN |
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1-283-16634-8 |
9786613166340 |
3-11-025021-7 |
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Descrizione fisica |
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1 online resource (404 p.) |
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Collana |
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De Gruyter series in nonlinear analysis and applications, , 0941-813X ; ; 13 |
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Classificazione |
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Altri autori (Persone) |
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Müller-WichardsD <1946-> (Dieter) |
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Disciplina |
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Soggetti |
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Stability - Mathematical models |
Mathematical optimization |
Orlicz spaces |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Front matter -- Preface -- Contents -- 1 Approximation in Orlicz Spaces -- 2 Polya Algorithms in Orlicz Spaces -- 3 Convex Sets and Convex Functions -- 4 Numerical Treatment of Non-linear Equations and Optimization Problems -- 5 Stability and Two-stage Optimization Problems -- 6 Orlicz Spaces -- 7 Orlicz Norm and Duality -- 8 Differentiability and Convexity in Orlicz Spaces -- 9 Variational Calculus -- Bibliography -- List of Symbols -- Index |
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Sommario/riassunto |
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This is an essentially self-contained book on the theory of convex functions and convex optimization in Banach spaces, with a special interest in Orlicz spaces. Approximate algorithms based on the stability principles and the solution of the corresponding nonlinear equations are developed in this text. A synopsis of the geometry of Banach spaces, aspects of stability and the duality of different levels of differentiability and convexity is developed. A particular emphasis is placed on the geometrical aspects of strong solvability of a convex optimization problem: it turns out that this property is equivalent to local uniform convexity of the corresponding convex function. This |
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