• DocumentCode
    504976
  • Title

    H2/H∞ approach to the histogram method for density estimation

  • Author

    Nagahara, M. ; Sato, K.I. ; Yamamoto, Y.

  • Author_Institution
    Grad. Sch. of Inf., Kyoto Univ., Kyoto, Japan
  • fYear
    2009
  • fDate
    18-21 Aug. 2009
  • Firstpage
    1230
  • Lastpage
    1233
  • Abstract
    In this paper, we study nonparametric density estimation by the histogram method. Histogram is interpreted as quantization, which decreases the amount of information. Then interpolation (or estimation) of the missing information is needed. To achieve this, we introduce sampled-data H2/Hinfin optimization. We design the reconstruction system which optimizes the worst case error between the original PDF and the estimation. The optimization is formulated by linear matrix inequalities and equalities. Numerical examples are illustrated to show effectiveness of our method.
  • Keywords
    Hinfin optimisation; interpolation; linear matrix inequalities; nonparametric statistics; quantisation (signal); sampled data filters; signal reconstruction; statistical distributions; PDF; histogram method; interpolation; linear matrix equality; linear matrix inequality; nonparametric density estimation; probability distribution; quantization; reconstruction system design; sampled-data H2/Hinfin optimization; worst case error; Control theory; Design optimization; Filters; Frequency; Histograms; Informatics; Interpolation; Optimization methods; Quantization; Symmetric matrices; Density estimation; histogram method; sampled-data control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    ICCAS-SICE, 2009
  • Conference_Location
    Fukuoka
  • Print_ISBN
    978-4-907764-34-0
  • Electronic_ISBN
    978-4-907764-33-3
  • Type

    conf

  • Filename
    5335078
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=504976