An improved algorithm for fractal estimation from noisy measurements

Author

Kaplan, Lance M. ; Kuo, C. C Jay

Author_Institution

Dept. of Electr. Eng.-Syst., California Univ., Los Angeles, CA, USA

Volume

4

fYear

1993

fDate

27-30 April 1993

Firstpage

89

Abstract

The authors first show that when the increments of sampled fractional Brownian motion (fBm), also known as discrete fractional Gaussian noise (DFGN), are set equal to the finest scale wavelet approximation coefficients and when the Haar basis is selected, the discrete wavelet transform (DWT) coefficients are weakly correlated and have a variance that is exponentially related to scale. The observation motivates a new fractal estimation algorithm, which is a variant of an algorithm introduced by Wornell and Oppenheim (IEEE Trans. vol.SP-40, no.3, p.611-23, March 1992) with the sampled fBm replaced by the increments of the sampled fBm. The performance of the new algorithm is compared with that of Wornell and Oppenheim´s algorithm in numerical simulation results.<>

Keywords

Brownian motion; estimation theory; fractals; sampled data systems; wavelet transforms; IEEE Trans; discrete wavelet transform; fractal estimation algorithm; noisy measurements; numerical simulation; sampled fractional Brownian motion; variance;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on

Conference_Location

Minneapolis, MN, USA

ISSN

1520-6149

Print_ISBN

0-7803-7402-9

Type

conf

DOI

10.1109/ICASSP.1993.319601

Filename

319601