The penalty term of Exponentially Embedded Family is estimated mutual information
Document Type
Conference Proceeding
Date of Original Version
6-16-2017
Abstract
The penalty term plays an important role in model order selection rules. The Exponentially Embedded Families (EEF) is consistent and effective in model order selection. In this paper we show that the EEF penalty term can be viewed as estimated mutual information (MI) between unknown parameters and received data from Bayesian viewpoints. The finding is a result of an important relationship between Kullback-Leibler Divergence (KLD), signal-to-noise ratio (SNR) and MI in estimation/detection of random signals, which is also introduced.
Publication Title, e.g., Journal
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Citation/Publisher Attribution
Zhu, Zhenghan, and Steven Kay. "The penalty term of Exponentially Embedded Family is estimated mutual information." ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (2017): 4149-4152. doi: 10.1109/ICASSP.2017.7952937.