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
Link To Document :
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