• DocumentCode
    2173931
  • Title

    N-Dimension Golden Section Search: Its Variants and Limitations

  • Author

    Chang, Yen-Ching

  • Author_Institution
    Dept. of Appl. Inf. Sci., Chung Shan Med. Univ., Taichung, Taiwan
  • fYear
    2009
  • fDate
    17-19 Oct. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    One-dimension (1-D) golden section search (GSS) is widely used in many fields. This algorithm is very suitable for searching without derivative for the extrema of objective functions with unimodal. Two-dimension (2-D) GSS was also implemented and used for object tracking. In this paper, a structured n-dimension GSS and its variants are proposed. It has been shown that 1-D GSS is the fastest algorithm except for Fibonacci search. However, the efficiency of n-dimension GSS, n > 1, is generally not the case. The phenomenon will be analyzed and experimented. In addition, the limitations of n-D GSS are also illustrated. These concepts are very important for the future use of GSS.
  • Keywords
    Fibonacci sequences; search problems; Fibonacci search; N-dimension golden section search; objective functions; Autocorrelation; Computational efficiency; Covariance matrix; Fractals; Gaussian noise; Parameter estimation; Probability density function; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4244-4132-7
  • Electronic_ISBN
    978-1-4244-4134-1
  • Type

    conf

  • DOI
    10.1109/BMEI.2009.5304779
  • Filename
    5304779