Distortion-rate functions for quantized compressive sensing
We study the average distortion introduced by quantizing compressive sensing measurements. Both uniform quantization and non-uniform quantization are considered. The asymptotic distortion-rate functions are obtained when the measurement matrix belongs to certain random matrix ensembles. Furthermore,...
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Published in | 2009 IEEE Information Theory Workshop on Networking and Information Theory pp. 171 - 175 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
01.06.2009
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ISBN | 1424445353 9781424445356 |
DOI | 10.1109/ITWNIT.2009.5158565 |
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Abstract | We study the average distortion introduced by quantizing compressive sensing measurements. Both uniform quantization and non-uniform quantization are considered. The asymptotic distortion-rate functions are obtained when the measurement matrix belongs to certain random matrix ensembles. Furthermore, we adapt two well-known compressive sensing reconstruction algorithms to accommodate the quantization effects. The performance of the new reconstruction methods is assessed through extensive computer simulations. |
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AbstractList | We study the average distortion introduced by quantizing compressive sensing measurements. Both uniform quantization and non-uniform quantization are considered. The asymptotic distortion-rate functions are obtained when the measurement matrix belongs to certain random matrix ensembles. Furthermore, we adapt two well-known compressive sensing reconstruction algorithms to accommodate the quantization effects. The performance of the new reconstruction methods is assessed through extensive computer simulations. |
Author | Milenkovic, O. Hoa Vinh Pham Wei Dai |
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Snippet | We study the average distortion introduced by quantizing compressive sensing measurements. Both uniform quantization and non-uniform quantization are... |
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SubjectTerms | Application software Computer simulation Distortion measurement Electric variables measurement Extraterrestrial measurements Image reconstruction Quantization Reconstruction algorithms Signal reconstruction Upper bound |
Title | Distortion-rate functions for quantized compressive sensing |
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