ICASSP 2006 - May 15-19, 2006 - Toulouse, France

Technical Program

Paper Detail

Paper:SPTM-P10.11
Session:Estimation
Time:Thursday, May 18, 16:30 - 18:30
Presentation: Poster
Topic: Signal Processing Theory and Methods: Detection, Estimation, Classification Theory and Applications
Title: On Maximum Likelihood Estimation in the Presence of Vanishing Information Measure
Authors: Ori Landau, Anthony Weiss, Tel-Aviv University, Israel
Abstract: We analyze the parameter estimation Mean Square Error when the Fisher Information Measure is zero at some points within the parameter space. At these points the CRLB diverges and no unbiased estimator can achieve a finite Mean Square Error. Under mild regularity conditions the Maximum Likelihood Estimator is known to be asymptotically unbiased and therefore lower bounded by the CRLB. It is therefore of interest to examine the Maximum Likelihood Estimator performance in the presence of vanishing Fisher Information Measure. We provide new theoretical and practical results. All results are corroborated by simulations.



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