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Minimax design of nonnegative finite impulse response filters.

Authors: Lai, Xiaoping; Xue, Anke; Lin, Zhiping; Lai, Chunlu;

Minimax design of nonnegative finite impulse response filters.

Abstract

Nonnegative impulse response (NNIR) filters have found many applications in signal processing and information fusion areas. Evidence filtering is one of the examples among others. An evidence filter is required to satisfy a nonnegativity condition and a normalization condition on its impulse response coefficients, and thus is basically an NNIR filter. This paper considers the design of nonnegative finite impulse response (FIR) filters based on frequency response approximation and proposes a constrained minimax design formulation using the fundamental limitations on the NNIR filter's frequency responses recently developed in the literature. The formulation is converted into a linearly constrained positive-definite quadratic programming and then solved with the Goldfarb-Idnani algorithm. The proposed method is applicable to nonnegative FIR lowpass as well as other types of filters. Design examples demonstrate the effectiveness of the proposed method.

Published version

Country
Singapore
Related Organizations
Keywords

DRNTU::Engineering::Electrical and electronic engineering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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