Abstract
A new definition of generalized information measures is introduced so as to investigate the finite-parameter estimation problem. This definition yields a class of generalized entropy functions which is useful for treating the error-probability of decision and the other equivocation measures such as Shannon's logarithmic measure in the same framework and, in particular, deriving upper bounds to the error-probability. A few of inequalities between these equivocation measures are presented including an extension of Fano's inequality.
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