A comparative investigation of information loss due to variable quantization on parameter estimation of compound distribution ?

摘要

In this paper we study the problem of how quantization may affect the maximum likelihood estimation of the parameters of a probability density function representing a compound distribution. We consider and compare three different approaches to design a variable quantizer allowing to guarantee a predefined loss of Fisher information which is used as a measure of the information loss due to quantization. We also propose the approximations which characterize the asymptotic behavior of the loss allowing a significant reduction of the computational complexity.