Abstract
This paper considers the problem of Bayesian estimation of a Gaussian vector in a linear model with random Gaussian uncertainty in the mixing matrix. The maximum a-posteriori estimator is derived for this model using the Bayesian expectation-maximization. It is demonstrated that the solution forms an elegant and simple iteration which can be easily implemented. Finally, the estimator developed is considered in the context of near-Gaussian-digitally modulated signals under channel uncertainty, where it is shown that the MAP estimator outperforms the standard linear MMSE estimator in terms of mean square error (MSE) and bit error rate (BER).
Original language | English |
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Title of host publication | 2008 IEEE International Conference on Acoustics, Speech and Signal Processing |
Publisher | IEEE |
Pages | 2889-2892 |
Number of pages | 4 |
ISBN (Print) | 9781424414833 |
DOIs | |
Publication status | Published - 12 May 2008 |
Event | 33rd IEEE International Conference on Acoustics, Speech and Signal Processing 2008 - Las Vegas, NV, USA, Las Vegas, United States Duration: 30 Mar 2008 → 4 Apr 2008 |
Conference
Conference | 33rd IEEE International Conference on Acoustics, Speech and Signal Processing 2008 |
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Abbreviated title | ICASSP 2008 |
Country/Territory | United States |
City | Las Vegas |
Period | 30/03/08 → 4/04/08 |