Dynamically-variable adaptive algorithms

Author

Morimoto, Jiro ; Kasamatsu, Hiroshi ; Yamamoto, Yoshikazu ; Kobayashi, Ikunori ; Furumoto, Nanayo ; Tabuchi, Toshiaki

Author_Institution

Fac. of Eng., Toskushima Bunri Univ., Kagawa, Japan

fYear

2001

fDate

2001

Firstpage

48

Lastpage

51

Abstract

Variations of the statistical properties of system inputs may cause a fall of adaptation abilities of the adaptive algorithms. To overcome this problem, we propose a dynamically-changing method of the form of the adaptive algorithms among Kalman filter based, normalized least mean square and recursive least squares methods. The validity of our method was confirmed in the numerical experiments

Keywords

Kalman filters; adaptive estimation; filtering theory; least mean squares methods; parameter estimation; tracking; Kalman filter based methods; LMS methods; NLMS methods; dynamically-variable adaptive algorithms; normalized least mean square methods; recursive least squares methods; statistical property variations; Adaptive algorithm; Algorithm design and analysis; Concrete; Design methodology; Kalman filters; Least squares methods; Noise measurement; Resonance light scattering; Time measurement; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers

Conference_Location

Nagoya

Print_ISBN

0-7803-7306-5

Type

conf

DOI

10.1109/SICE.2001.977804

Filename

977804