Nonlinear phase FIR filter design with minimum LS error and additional constraints
| dc.citation.bibtexName | article | en_US |
| dc.citation.journalTitle | EURASIP Signal Processing | en_US |
| dc.contributor.author | Lang, Markus | en_US |
| dc.contributor.author | Bamberger, Joachim | en_US |
| dc.contributor.org | Digital Signal Processing (http://dsp.rice.edu/) | en_US |
| dc.date.accessioned | 2007-10-31T00:50:55Z | |
| dc.date.available | 2007-10-31T00:50:55Z | |
| dc.date.issued | 1994-07-01 | en |
| dc.date.modified | 2004-11-11 | en_US |
| dc.date.submitted | 2004-11-08 | en_US |
| dc.description | Journal Paper | en_US |
| dc.description.abstract | We examine the problem of approximating a complex frequency response by a real-valued FIR filter according to the <i>L<sub>2</sub></i> norm subject to additional inequality constraints for the complex error function. Starting with the Kuhn-Tucker optimality conditions which specialize to a system of nonlinear equations we deduce an iterative algorithm. These equations are solved by Newton's method in every iteration step. The algorithm allows arbitrary tradeoffs between an <i>L<sub>2</sub></i> and an <i>L<sub>oo</sub></i> design. The <i>L<sub>2</sub></i> and the <i>L<sub>oo</sub></i> solution result as special cases. | en_US |
| dc.identifier.citation | M. Lang and J. Bamberger, "Nonlinear phase FIR filter design with minimum LS error and additional constraints," <i>EURASIP Signal Processing,</i> 1994. | |
| dc.identifier.doi | http://dx.doi.org/10.1109/ICASSP.1993.319434 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/20044 | |
| dc.language.iso | eng | |
| dc.subject | filter design | * |
| dc.subject.keyword | filter design | en_US |
| dc.subject.other | Filter Design | en_US |
| dc.title | Nonlinear phase FIR filter design with minimum LS error and additional constraints | en_US |
| dc.type | Journal article | |
| dc.type.dcmi | Text |
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