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Autor(en): 
  • Simon Dan
  • Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches 
     

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


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Juli 2006  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Across / Advanced / amount / Approach / Author / book / bottomup / confidently
    ISBN:  9780471708582 
    EAN-Code: 
    9780471708582 
    Verlag:  Wiley 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 262 mm / B 185 mm / D 36 mm 
    Gewicht:  1170 gr 
    Seiten:  552 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    A bottom-up approach that enables readers to master and apply the latest techniques in state estimation

    This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering.

    While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning:

    • Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation
    • Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice
    • MATLAB®-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters

    Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering.

    Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. A solutions manual is available for instructors.

    With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.

      



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