Adaptive predictors in cascade form to analyse superimposed exponential signals with time-varying parameters

Julio Vargas, Steve McLaughlin

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Abstract

In this paper adaptive predictors structured in cascade form are used to analyse superimposed exponential signals with time-varying parameters. On-line optimisation of the filters parameters is achieved using gradient descent techniques focused on the direct estimation of instantaneous information-bearing parameters (damping and frequency). Examples of the performance of the algorithm are given for real-valued multi-component synthetic signals with different schemes of frequency modulation in clean and noisy environments. The performance of the algorithm is also evaluated in the task of tracking the formants of a voiced segment of speech. (C) 2001 Elsevier Science BY. All rights reserved.

Original languageEnglish
Pages (from-to)2223-2233
Number of pages11
JournalSignal Processing
Volume81
Issue number10
DOIs
Publication statusPublished - Oct 2001

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