Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/93910
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Title: Design of sparse filters by a discrete filled function technique
Authors: Feng, ZG
Yiu, KFC 
Wu, SY
Issue Date: Oct-2018
Source: Circuits, systems and signal processing, Oct. 2018, v. 37, no. 10, p. 4279-4294
Abstract: In this paper, we consider the sparse filter design problem where some of the coefficients can be reduced to zeroes in order to lower implementation complexity. The objective is to choose the fewest number of nonzero filter coefficients to meet a given performance requirement. We formulate a discrete optimization problem to minimize the number of nonzero terms and develop a discrete search method to find the minimal nonzero terms. In each step, we need to consider a subproblem to design the filter coefficients with a given set of nonzero terms. We formulate this subproblem as a linear programming problem and apply an exchange algorithm to find the optimal coefficients. For illustration, we compare the proposed algorithm with existing methods and show that the proposed method gives better results in all our test cases.
Keywords: Discrete search method
Filled function
Sparse filter design
Publisher: Birkhäuser
Journal: Circuits, systems and signal processing
ISSN: 0278-081X
EISSN: 1531-5878
DOI: 10.1007/s00034-018-0758-z
Rights: © Springer Science+Business Media, LLC, part of Springer Nature 2018
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s00034-018-0758-z
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