Global optimal design of IIR filters via constraint transcription and filled function methods
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...
| Main Authors: | , , , |
|---|---|
| Format: | Journal Article |
| Published: |
SP Birkhäuser Verlag
2013
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/24066 |
| _version_ | 1848751326049075200 |
|---|---|
| author | Ling, B. Wu, C. Teo, Kok Lay Rehbock, Volker |
| author_facet | Ling, B. Wu, C. Teo, Kok Lay Rehbock, Volker |
| author_sort | Ling, B. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T07:50:57Z |
| format | Journal Article |
| id | curtin-20.500.11937-24066 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:50:57Z |
| publishDate | 2013 |
| publisher | SP Birkhäuser Verlag |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-240662017-09-13T15:33:37Z Global optimal design of IIR filters via constraint transcription and filled function methods Ling, B. Wu, C. Teo, Kok Lay Rehbock, Volker constraint transcription global optimization IIR filter design filled function 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. 2013 Journal Article http://hdl.handle.net/20.500.11937/24066 10.1007/s00034-012-9511-1 SP Birkhäuser Verlag restricted |
| spellingShingle | constraint transcription global optimization IIR filter design filled function Ling, B. Wu, C. Teo, Kok Lay Rehbock, Volker Global optimal design of IIR filters via constraint transcription and filled function methods |
| title | Global optimal design of IIR filters via constraint transcription and filled function methods |
| title_full | Global optimal design of IIR filters via constraint transcription and filled function methods |
| title_fullStr | Global optimal design of IIR filters via constraint transcription and filled function methods |
| title_full_unstemmed | Global optimal design of IIR filters via constraint transcription and filled function methods |
| title_short | Global optimal design of IIR filters via constraint transcription and filled function methods |
| title_sort | global optimal design of iir filters via constraint transcription and filled function methods |
| topic | constraint transcription global optimization IIR filter design filled function |
| url | http://hdl.handle.net/20.500.11937/24066 |