Optimal quantization for compressive sensing under message passing reconstruction
We consider the optimal quantization of compressive sensing measurements along with estimation from quantized samples using generalized approximate message passing (GAMP). GAMP is an iterative reconstruction scheme inspired by the belief propagation algorithm on bipartite graphs which generalizes ap...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2012
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| Online Access: | http://hdl.handle.net/1721.1/73036 |
| _version_ | 1826200386073001984 |
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| author | Kamilov, Ulugbek Goyal, Vivek K. Rangan, Sundeep |
| author2 | Massachusetts Institute of Technology. Research Laboratory of Electronics |
| author_facet | Massachusetts Institute of Technology. Research Laboratory of Electronics Kamilov, Ulugbek Goyal, Vivek K. Rangan, Sundeep |
| author_sort | Kamilov, Ulugbek |
| collection | MIT |
| description | We consider the optimal quantization of compressive sensing measurements along with estimation from quantized samples using generalized approximate message passing (GAMP). GAMP is an iterative reconstruction scheme inspired by the belief propagation algorithm on bipartite graphs which generalizes approximate message passing (AMP) for arbitrary measurement channels. Its asymptotic error performance can be accurately predicted and tracked through the state evolution formalism. We utilize these results to design mean-square optimal scalar quantizers for GAMP signal reconstruction and empirically demonstrate the superior error performance of the resulting quantizers. |
| first_indexed | 2024-09-23T11:35:35Z |
| format | Article |
| id | mit-1721.1/73036 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:35:35Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/730362022-09-27T20:32:37Z Optimal quantization for compressive sensing under message passing reconstruction Kamilov, Ulugbek Goyal, Vivek K. Rangan, Sundeep Massachusetts Institute of Technology. Research Laboratory of Electronics Goyal, Vivek K. Kamilov, Ulugbek Goyal, Vivek K. We consider the optimal quantization of compressive sensing measurements along with estimation from quantized samples using generalized approximate message passing (GAMP). GAMP is an iterative reconstruction scheme inspired by the belief propagation algorithm on bipartite graphs which generalizes approximate message passing (AMP) for arbitrary measurement channels. Its asymptotic error performance can be accurately predicted and tracked through the state evolution formalism. We utilize these results to design mean-square optimal scalar quantizers for GAMP signal reconstruction and empirically demonstrate the superior error performance of the resulting quantizers. 2012-09-18T15:18:42Z 2012-09-18T15:18:42Z 2011-10 2011-07 Article http://purl.org/eprint/type/ConferencePaper 978-1-4577-0594-6 978-1-4577-0596-0 2157-8095 http://hdl.handle.net/1721.1/73036 Kamilov, Ulugbek, Vivek K Goyal, and Sundeep Rangan. “Optimal Quantization for Compressive Sensing Under Message Passing Reconstruction.” IEEE International Symposium on Information Theory Proceedings (ISIT), 2011. 459–463. en_US http://dx.doi.org/10.1109/ISIT.2011.6034168 Proceedings of the IEEE International Symposium on Information Theory Proceedings (ISIT), 2011 Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) arXiv |
| spellingShingle | Kamilov, Ulugbek Goyal, Vivek K. Rangan, Sundeep Optimal quantization for compressive sensing under message passing reconstruction |
| title | Optimal quantization for compressive sensing under message passing reconstruction |
| title_full | Optimal quantization for compressive sensing under message passing reconstruction |
| title_fullStr | Optimal quantization for compressive sensing under message passing reconstruction |
| title_full_unstemmed | Optimal quantization for compressive sensing under message passing reconstruction |
| title_short | Optimal quantization for compressive sensing under message passing reconstruction |
| title_sort | optimal quantization for compressive sensing under message passing reconstruction |
| url | http://hdl.handle.net/1721.1/73036 |
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