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Global Optimal Design of IIR Filters via Constraint Transcription and Filled Function Methods

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Abstract

In this paper, we consider a globally optimal design of IIR filters. We formulate the design problem as a nonconvex optimization problem with a continuous inequality constraint and a nonconvex constraint. To solve this problem, the constraint transcription method is applied to tackle the continuous inequality constraint. In order to avoid the obtained solution being on the boundary of the feasible set, more than one initial points are used. Moreover, since the objective and the constraints are nonconvex functions, there may be many local minima. To address this problem, the filled function method is applied to escape from the local minima. Some numerical computer simulation results are presented to illustrate the effectiveness and efficiency of the proposed method.

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Authors and Affiliations

  1. Faculty of Information Engineering, Guangdong University of Technology, Guangzhou, 510006, China

    B. W. K. Ling

  2. School of Mathematics and Computer Science, Chongqing Normal University, Chongqing, 401331, China

    C. Z. Wu

  3. Department of Mathematics and Statistics, Curtin University, Perth, Western Australia, WA6012, Australia

    K. L. Teo & V. Rehbock

Authors
  1. B. W. K. Ling
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  2. C. Z. Wu
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  3. K. L. Teo
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  4. V. Rehbock
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Correspondence to B. W. K. Ling.

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Ling, B.W.K., Wu, C.Z., Teo, K.L. et al. Global Optimal Design of IIR Filters via Constraint Transcription and Filled Function Methods. Circuits Syst Signal Process 32, 1313–1334 (2013). https://doi.org/10.1007/s00034-012-9511-1

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  • DOI: https://doi.org/10.1007/s00034-012-9511-1

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