The AR modeling is widely used in signal processing. The coefficients of AR model can be easily obtained by a LMS prediction error filter. However, it is known that such filter will give bias coefficients when the input signal is corrupted by noise. In previous works, Treicher  suggested the γ-LMS algorithm to reduce the bias problem caused by Gaussian noise. This paper gives the theoretical analysis of the γ-LMS algorithm. We derive the close form solution of the second order statistics of the tap-weight vector. Computer simulation are provided to show the accuracy of our theoretical results.
|Number of pages||6|
|State||Published - 1 Dec 1994|
|Event||Proceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems - Taipei, Taiwan|
Duration: 5 Dec 1994 → 8 Dec 1994
|Conference||Proceedings of the 1994 IEEE Asia-Pacific Conference on Circuits and Systems|
|Period||5/12/94 → 8/12/94|