/

Filtering Additive Measurement Noise with Maximum Entropy in the Mean

Henryk Gzyl, Enrique ter Horst
Arxiv ID: 0709.0509Last updated: 8/23/2021
The purpose of this note is to show how the method of maximum entropy in the mean (MEM) may be used to improve parametric estimation when the measurements are corrupted by large level of noise. The method is developed in the context on a concrete example: that of estimation of the parameter in an exponential distribution. We compare the performance of our method with the bayesian and maximum likelihood approaches.

PaperStudio AI Chat

I'm your research assistant! Ask me anything about this paper.
About
Pricing
Commercial Disclosure
Contact
© 2023 Paper Studio™. All Rights Reserved.