Robust Parameter Estimators for Communication Data
RICE UNIV HOUSTON TX DEPT OF ELECTRICAL ENGINEERING
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The object of this grant is the analysis and design of decision procedures that have stable, good performance in statistically ill-defined environments. Such procedures indicate the way to design powerful receivers for systems whose statistical behavior cannot be described precisely due to incomplete availability of data about the system behavior. Different distance measures have been studied for use as performance criteria for robust estimates. Careful evaluation and comparison of these distances was done and their similarities, advantages and disadvantages were carefully stated. A thorough study of the work already accomplished by the author as well as other investigators on nonparametric statistical procedures in the presence of small number of discrete data was done and included in a book on the use of nonparametric procedures in Communication Systems. A feature selection problem was studied, when several distance measures are used as discrimination criteria. A sequential procedure for clustered data was proposed and analyzed. Hampels general qualitative definition of robustness of sequences of estimators on memoryless observation processes was generalized to stationary processes. The constructive analysis of robustness completed by the author is being used now in the performance analysis of communication Networks at Bell Laboratories.
- Statistics and Probability
- Non-Radio Communications