@inproceedings{2df815ab20584499a3ab694c931c0966,
title = "A new recursive algorithm for time-varying autoregressive (TVAR) model estimation and its application to speech analysis",
abstract = "This paper proposes a new state-regularized (SR) and QR decomposition based recursive least squares (QRRLS) algorithm with variable forgetting factor (VFF) for recursive coefficient estimation of time-varying autoregressive (AR) models. It employs the estimated coefficients as prior information to minimize the exponentially weighted observation error, which leads to reduced variance and bias over traditional regularized RLS algorithm. It also increases the tracking speed by introducing a new measure of convergence status to control the FF. Simulations using synthetic and real speech signals show that the proposed method has improved tracking performance and reduced estimation error variance than conventional TVAR modeling methods during rapid changing of AR coefficients.",
author = "Chu, \{Y. J.\} and Chan, \{S. C.\} and Zhang, \{Z. G.\} and Tsui, \{K. M.\}",
year = "2012",
doi = "10.1109/ISCAS.2012.6271402",
language = "英语",
series = "ISCAS 2012 - 2012 IEEE International Symposium on Circuits and Systems",
publisher = "IEEE Computer Society",
pages = "1026--1029",
booktitle = "ISCAS 2012 - 2012 IEEE International Symposium on Circuits and Systems",
address = "美国",
note = "2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 ; Conference date: 20-05-2012 Through 23-05-2012",
}