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Steady-State Performance Limitations of Subband Adaptive Filters

Steady-State Performance Limitations of Subband Adaptive Filters
Steady-State Performance Limitations of Subband Adaptive Filters
Non-perfect filter banks used for subband adaptive filtering (SAF) are known to impose limitations on the steady-state performance of such systems. In this paper, we quantify the minimum mean-square error (MMSE) and the accuracy with which the overall SAF system can model an unknown system that it is set to identify. Firstly, in case of MMSE limits, the error is evaluated based on a power spectral density description of aliased signal components, which is accessible via a source model for the subband signals that we derive. Approximations of the MMSE can be embedded in a signal-to-alias ratio (SAR), a factor by which the error power can be reduced by adaptive filtering. With simplifications, SAR only depends on the filter banks. Secondly, in case of modelling, we link the accuracy of the SAF system to the filter bank mismatch in perfect reconstruction. When using modulated filter banks, both error limits --- MMSE and inaccuracy --- can be linked to the prototype. We explicitly derive this for generalized DFT modulated filter banks and demonstrate the validity of the analytical error limits and their approximations for a number of examples, whereby the analytically predicted limits of error quantities compare favourably with simulations.
1053-587X
1982-91
Weiss, S
a1716781-351d-41d2-8d67-3e3d34f16476
Stenger, A
9dba20db-8ca7-41fe-8b30-dad4ab2f93c5
Stewart, RW
2b292fcf-ba56-4c96-b051-086c2df26c4c
Rabenstein, R
4ac34477-f962-446e-b47d-0e66df88935c
Weiss, S
a1716781-351d-41d2-8d67-3e3d34f16476
Stenger, A
9dba20db-8ca7-41fe-8b30-dad4ab2f93c5
Stewart, RW
2b292fcf-ba56-4c96-b051-086c2df26c4c
Rabenstein, R
4ac34477-f962-446e-b47d-0e66df88935c

Weiss, S, Stenger, A, Stewart, RW and Rabenstein, R (2001) Steady-State Performance Limitations of Subband Adaptive Filters. IEEE Transactions on Signal Processing, 49 (9), 1982-91.

Record type: Article

Abstract

Non-perfect filter banks used for subband adaptive filtering (SAF) are known to impose limitations on the steady-state performance of such systems. In this paper, we quantify the minimum mean-square error (MMSE) and the accuracy with which the overall SAF system can model an unknown system that it is set to identify. Firstly, in case of MMSE limits, the error is evaluated based on a power spectral density description of aliased signal components, which is accessible via a source model for the subband signals that we derive. Approximations of the MMSE can be embedded in a signal-to-alias ratio (SAR), a factor by which the error power can be reduced by adaptive filtering. With simplifications, SAR only depends on the filter banks. Secondly, in case of modelling, we link the accuracy of the SAF system to the filter bank mismatch in perfect reconstruction. When using modulated filter banks, both error limits --- MMSE and inaccuracy --- can be linked to the prototype. We explicitly derive this for generalized DFT modulated filter banks and demonstrate the validity of the analytical error limits and their approximations for a number of examples, whereby the analytically predicted limits of error quantities compare favourably with simulations.

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More information

Published date: September 2001
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 255737
URI: http://eprints.soton.ac.uk/id/eprint/255737
ISSN: 1053-587X
PURE UUID: 219bd53f-7a62-45d8-8e30-eee4818c4528

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Date deposited: 18 Sep 2001
Last modified: 08 Jan 2022 14:41

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Contributors

Author: S Weiss
Author: A Stenger
Author: RW Stewart
Author: R Rabenstein

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