On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based Recursions
Error-feedback, normalized, and array-based recursions represent equivalent RLS lattice adaptive filters which are known to offer better numerical properties under finite-precision implementations. This is the case when the underlying data structure arises from a tapped-delay-line model for the inpu...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2005-05-01
|
| Series: | EURASIP Journal on Advances in Signal Processing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1155/ASP.2005.1235 |
| _version_ | 1818127404833439744 |
|---|---|
| author | Ricardo Merched |
| author_facet | Ricardo Merched |
| author_sort | Ricardo Merched |
| collection | DOAJ |
| description | Error-feedback, normalized, and array-based recursions represent equivalent RLS lattice adaptive filters which are known to offer better numerical properties under finite-precision implementations. This is the case when the underlying data structure arises from a tapped-delay-line model for the input signal. On the other hand, in the context of a more general orthonormality-based input model, these variants have not yet been derived and their behavior under finite precision is unknown. This paper develops several lattice structures for the exponentially weighted RLS problem under orthonormality-based data structures, including error-feedback, normalized, and array-based forms. As a result, besides nonminimality of the new recursions, they present unstable modes as well as hyperbolic rotations, so that the well-known good numerical properties observed in the case of FIR models no longer exist. We verify via simulations that, compared to the standard extended lattice equations, these variants do not improve the robustness to quantization, unlike what is normally expected for FIR models. |
| first_indexed | 2024-12-11T07:16:49Z |
| format | Article |
| id | doaj.art-2f7673f438034f5f801040654353fb4a |
| institution | Directory Open Access Journal |
| issn | 1687-6172 1687-6180 |
| language | English |
| last_indexed | 2024-12-11T07:16:49Z |
| publishDate | 2005-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-2f7673f438034f5f801040654353fb4a2022-12-22T01:16:13ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802005-05-01200581235125010.1155/ASP.2005.1235On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based RecursionsRicardo MerchedError-feedback, normalized, and array-based recursions represent equivalent RLS lattice adaptive filters which are known to offer better numerical properties under finite-precision implementations. This is the case when the underlying data structure arises from a tapped-delay-line model for the input signal. On the other hand, in the context of a more general orthonormality-based input model, these variants have not yet been derived and their behavior under finite precision is unknown. This paper develops several lattice structures for the exponentially weighted RLS problem under orthonormality-based data structures, including error-feedback, normalized, and array-based forms. As a result, besides nonminimality of the new recursions, they present unstable modes as well as hyperbolic rotations, so that the well-known good numerical properties observed in the case of FIR models no longer exist. We verify via simulations that, compared to the standard extended lattice equations, these variants do not improve the robustness to quantization, unlike what is normally expected for FIR models.http://dx.doi.org/10.1155/ASP.2005.1235RLS algorithmorthonormal modellatticeregularized least squares. |
| spellingShingle | Ricardo Merched On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based Recursions EURASIP Journal on Advances in Signal Processing RLS algorithm orthonormal model lattice regularized least squares. |
| title | On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based Recursions |
| title_full | On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based Recursions |
| title_fullStr | On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based Recursions |
| title_full_unstemmed | On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based Recursions |
| title_short | On Extended RLS Lattice Adaptive Variants: Error-Feedback, Normalized, and Array-Based Recursions |
| title_sort | on extended rls lattice adaptive variants error feedback normalized and array based recursions |
| topic | RLS algorithm orthonormal model lattice regularized least squares. |
| url | http://dx.doi.org/10.1155/ASP.2005.1235 |
| work_keys_str_mv | AT ricardomerched onextendedrlslatticeadaptivevariantserrorfeedbacknormalizedandarraybasedrecursions |