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Autor(en): 
  • Jiongmin Yong
  • Jingrui Sun
  • Stochastic Linear-Quadratic Optimal Control Theory: Open-Loop and Closed-Loop Solutions 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juni 2020  
    Genre:  Schulbücher 
     
    C / Calculus of variations / Calculus of Variations and Optimal Control; Optimization / Calculus of Variations and Optimization / Cybernetics & systems theory / game theory / Game Theory, Economics, Social and Behav. Sciences / Mathematics and Statistics
    ISBN:  9783030209216 
    EAN-Code: 
    9783030209216 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  SpringerBriefs in Mathematics  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  221 gr 
    Seiten:  120 
    Illustration:  XIV, 120 p. 3 illus., 1 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:


    This book gathers the most essential results, including recent ones, on linear-quadratic optimal control problems, which represent an important aspect of stochastic control. It presents the results in the context of finite and infinite horizon problems, and discusses a number of new and interesting issues. Further, it precisely identifies, for the first time, the interconnections between three well-known, relevant issues - the existence of optimal controls, solvability of the optimality system, and solvability of the associated Riccati equation. Although the content is largely self-contained, readers should have a basic grasp of linear algebra, functional analysis and stochastic ordinary differential equations. The book is mainly intended for senior undergraduate and graduate students majoring in applied mathematics who are interested in stochastic control theory. However, it will also appeal to researchers in other related areas, such as engineering, management, finance/economics and the social sciences.


      



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