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Title: | The application of genetic algorithms to the adaptation of IIR filters |
Authors: | Ma, Qiang |
Issue Date: | 1995 |
Publisher: | © Qiang Ma |
Abstract: | The adaptation of an IIR filter is a very difficult problem due to its non-quadratic
performance surface and potential instability. Conventional adaptive IIR algorithms
suffer from potential instability problems and a high cost for stability
monitoring. Therefore, there is much interest in adaptive IIR filters based on alternative
algorithms. Genetic algorithms are a family of search algorithms based
on natural selection and genetics. They have been successfully used in many different
areas. Genetic algorithms applied to the adaptation of IIR filtering problems
are studied in this thesis, and show that the genetic algorithm approach has a
number of advantages over conventional gradient algorithms, particularly, for the
adaptation of high order adaptive IIR filters, IIR filters with poles close to the
unit circle and IIR filters with multi-modal error surfaces. The conventional gradient
algorithms have difficulty solving these problems. Coefficient results are
presented for various orders of IIR filters in this thesis. In the computer simulations
presented in this thesis, the direct, cascade, parallel and lattice form IIR
filter structures have been used and compared. The lattice form IIR filter structure
shows its superiority over the cascade and parallel form IIR filter structures
in terms of its mean square error convergence performance. |
Description: | A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy at Loughborough University. |
URI: | https://dspace.lboro.ac.uk/2134/32269 |
Appears in Collections: | PhD Theses (Mechanical, Electrical and Manufacturing Engineering)
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