A CASCADE LATTICE IIR ADAPTIVE FILTER FOR TOTAL LEAST-SQUARES PROBLEM

In many actual applications of the adaptive filtering, input signals a s well as output signals often contain observation noises. Hence, it i s necessary to develop an adaptive filtering algorithm to such an erro rs-in-variables (EIV) model. One solution for identifying the EIV mode l is a total least squares (TLS) algorithm based on a singular value d ecomposition of an off-line processing. However, it has not been consi dered to identify the EIV IIR system using an adaptive TLS algorithm o f which stability has been guaranteed during adaptation process. Hence we propose a normalized lattice IIR adaptive filtering algorithm for the TLS parameter estimation. We also show the effectiveness of the pr oposed algorithm under noisy circumstances through simulations.