On the sparse beamformer design
In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation. Moreover, the size of t...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
MDPI Publishing
2018
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| Online Access: | http://hdl.handle.net/20.500.11937/71572 |
| _version_ | 1848762515865993216 |
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| author | Gao, M. Yiu, K. Nordholm, Sven |
| author_facet | Gao, M. Yiu, K. Nordholm, Sven |
| author_sort | Gao, M. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation. Moreover, the size of the array can also be pruned to reduce complexity. These problems are addressed in this paper. A suitable optimization model is proposed. Both array pruning and filter thinning can be solved together as a two-stage optimization problem to yield the final sparse designs. Numerical results show that the complexity of the designed beamformers can be reduced significantly with minimal effect on performance. |
| first_indexed | 2025-11-14T10:48:48Z |
| format | Journal Article |
| id | curtin-20.500.11937-71572 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:48:48Z |
| publishDate | 2018 |
| publisher | MDPI Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-715722019-01-15T03:01:22Z On the sparse beamformer design Gao, M. Yiu, K. Nordholm, Sven In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation. Moreover, the size of the array can also be pruned to reduce complexity. These problems are addressed in this paper. A suitable optimization model is proposed. Both array pruning and filter thinning can be solved together as a two-stage optimization problem to yield the final sparse designs. Numerical results show that the complexity of the designed beamformers can be reduced significantly with minimal effect on performance. 2018 Journal Article http://hdl.handle.net/20.500.11937/71572 10.3390/s18103536 http://creativecommons.org/licenses/by/4.0/ MDPI Publishing fulltext |
| spellingShingle | Gao, M. Yiu, K. Nordholm, Sven On the sparse beamformer design |
| title | On the sparse beamformer design |
| title_full | On the sparse beamformer design |
| title_fullStr | On the sparse beamformer design |
| title_full_unstemmed | On the sparse beamformer design |
| title_short | On the sparse beamformer design |
| title_sort | on the sparse beamformer design |
| url | http://hdl.handle.net/20.500.11937/71572 |