Natural gradient adaptation is an especially convenient method for adapting the coefficients of a linear system in inverse filtering tasks such as blind deconvolution and equalization. Practical implementations of such methods require truncation of the filter impulse responses within the gradient updates. In this paper, we show how truncation of these filter impulse responses can create convergence problems and introduces a bias into the steady-state solution of one such algorithm. We then show how this algorithm can be modified to effectively mitigate these effects for estimating causal FIR approximations to doubly-infinite IIR equalizers. Simulations indicate that the modified algorithm provides the convergence benefits of the natural gradient while still attaining good steady-state performance.
|ジャーナル||Conference Record of the Asilomar Conference on Signals, Systems and Computers|
|出版ステータス||Published - 2003|
|イベント||Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States|
継続期間: 2003 11月 9 → 2003 11月 12
ASJC Scopus subject areas
- コンピュータ ネットワークおよび通信