**2**Author(s)

A fundamental relationship exists between the quality of an adaptive solution and the amount of data used in obtaining it. Quality is defined here in terms of "misadjustment," the ratio of the excess mean square error (mse) in an adaptive solution to the minimum possible mse. The higher the misadjustment, the lower the quality is. The quality of the exact least squares solution is compared with the quality of the solutions obtained by the orthogonalized and the conventional least mean square (LMS) algorithms with stationary and nonstationary input data. When adapting with noisy observations, a filter trained with a finite data sample using an exact least squares algorithms will have a misadjustment given by

- Page(s):
- 211 - 221
- ISSN :
- 0018-9448
- DOI:
- 10.1109/TIT.1984.1056892

- Date of Current Version :
- 06 January 2003
- Issue Date :
- Mar 1984
- Sponsored by :
- IEEE Information Theory Society
- Publisher:
- IEEE