Numerical characteristics of fast recursive least squares transversal adaptation algorithms - A comparative study
暂无分享,去创建一个
[1] A. Benallal,et al. A new method to stabilize fast RLS algorithms based on a first-order of the propagation of numerical errors , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.
[2] L. Ljung,et al. Fast calculation of gain matrices for recursive estimation schemes , 1978 .
[3] S. Ljung. Fast Algorithms for Integral Equations and Least Squares Identification Problems , 1983 .
[4] George Carayannis,et al. A fast sequential algorithm for least-squares filtering and prediction , 1983 .
[5] S. T. Alexander,et al. Adaptive Signal Processing: Theory and Applications , 1986 .
[6] Lennart Ljung,et al. Error propagation properties of recursive least-squares adaptation algorithms , 1985, Autom..
[7] P. Fabre,et al. Improvement of the fast recursive least-squares algorithms via normalization: A comparative study , 1986, IEEE Trans. Acoust. Speech Signal Process..
[8] G. Moustakides. Correcting the instability due to finite precision of the fast Kalman identification algorithms , 1989 .
[9] D. Lin. On digital implementation of the fast kalman algorithms , 1984 .
[10] T. Kailath,et al. Fast, recursive-least-squares transversal filters for adaptive filtering , 1984 .
[11] T. Kailath,et al. Numerically stable fast transversal filters for recursive least squares adaptive filtering , 1991, IEEE Trans. Signal Process..