Normalized estimate of adaptive filter for non-minimum phase transfer function component: An illustrative case study

Authors:
Jinsoo Jeong
Affiliations:
-
Venue:
Neurocomputing
Year:
2014

Citing 7
Cited 0

Adaptive signal processing

Adaptive signal processing
Adaptive filter theory (3rd ed.)

Adaptive filter theory (3rd ed.)
A combined blind source separation and adaptive noise cancellation scheme with potential application in blind acoustic parameter extraction

Neurocomputing
A real-time kepstrum approach to speech enhancement and noise cancellation

Neurocomputing
Signal denoising in engineering problems through the minimum gradient method

Neurocomputing
Dual channel based speech enhancement using novelty filter for robust speech recognition in automobile environment

IEEE Transactions on Consumer Electronics
Speech enhancement strategy for speech recognition microcontroller under noisy environments

Neurocomputing

Quantified Score

Hi-index	0.01

Visualization

Abstract

This paper presents an analysis of a normalized estimate of an adaptive finite impulse response (FIR) filter for a non-minimum phase transfer function component for the application of a minimum phase kepstrum filter (a ratio of minimum phase filters) to a one-sample delay filter in a beamforming structure. Based on the analysis, it will be shown that a normalized estimate by an adaptive FIR filter is characterized as only one non-minimum phase term from an unknown non-minimum phase system because the adaptive FIR filter estimates a consistent non-minimum phase term in a normalized form from both direct transfer function and its inverted transfer function. Furthermore, it will be shown that the characterized non-minimum phase term from the estimate by the adaptive FIR filter can identify an actual non-minimum phase transfer function component that can be used to evaluate the reverberant level in a realistic environment by monitoring only one zero position from pole-zero placements.