| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] Univ Estadual Campinas, Sch Appl Sci, Campinas, SP - Brazil
[2] State Univ West Parana, Ctr Exact Sci & Engn, Foz Do Iguacu, PR - Brazil
[3] Univ Estadual Campinas, Inst Math, Campinas, SP - Brazil
Total Affiliations: 3
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| Document type: | Review article |
| Source: | JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS; v. 353, n. 3, p. 643-656, FEB 2016. |
| Web of Science Citations: | 0 |
| Abstract | |
We consider the quadratic Gaussian CEO problem, where the goal is to estimate a measure based on several Gaussian noisy observations which must be encoded and sent to a centralized receiver using limited transmission rate. For real applications, besides minimizing the average distortion, given the transmission rate, it is important to take into account memory and processing constraints. Considering these motivations, we present a low complexity coding and decoding strategy, which exploits the correlation between the measurements to reduce the number of bits to be transmitted by refining the output of the quantization stage. The CEO makes an estimate using a decoder based on a process similar to majority voting. We derive explicit expression for the CEO's error probability and compare numerical simulations with known achievability results and bounds. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 13/25977-7 - Security and reliability of Information: theory and practice |
| Grantee: | Marcelo Firer |
| Support Opportunities: | Research Projects - Thematic Grants |