Title :
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
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;
Conference_Titel :
SICE 2001. Proceedings of the 40th SICE Annual Conference. International Session Papers
Conference_Location :
Nagoya
Print_ISBN :
0-7803-7306-5
DOI :
10.1109/SICE.2001.977804
