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Robust Equalizer Design for Allpass Transformed DFT Filter Banks with LTI Property

Authors:
Fabian Altenbach, Heinrich W. Löllmann, and Rudolf Mathar
Book Title:
Proceedings of IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)
Venue:
Istanbul, Turkey
Event Date:
26.-29.9.2010
Organization:
IEEE
Date:
Sept. 2010
Pages:
864–850
Language:
English

Abstract

Allpass transformed filter banks provide a nonuniform

frequency resolution and can be used in mobile speech

processing systems, e.g., cellular phones or digital hearing aids.

The nominal design of such an allpass transformed analysissynthesis

filter bank (AS FB) with near perfect reconstruction

(NPR) is achieved by numerical optimization of finite-impulse

response (FIR) equalizers in each subchannel. The underlying

nominal optimization problem is an equality constrained leastsquares

problem. In a robust design, we take into account

coefficient uncertainty in a possible implementation of such a

filter bank. We will describe this uncertainty by the choice of two

simple set-based worst-case uncertainty models, namely a norm

bound error model and a coefficient bound error model. When

including these error models, both robust designs can be recast

as second-order cone programs (SOCP) and solved efficiently

by standard numerical optimization methods. Furthermore, we

will provide design examples to show that both robust designs

maintain a good overall performance with respect to NPR while

offering less sensitivity to quantization errors.

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