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By John G. Webster (Editor)

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Int. Conf. Inf. Sci. , Piscataway, NJ: IEEE Press, 1976. 29. J. D. Johnson, A filter family designed for use in quadrature mirror filter banks, Proc. IEEE Int. Conf. , Piscataway, NJ: IEEE Press, 1980, pp. 291–294. 696 DATA-FLOW AND MULTITHREADED ARCHITECTURES 30. M. J. T. Smith and T. P. Barnwell III, A procedure for designing exact reconstruction filter banks for tree structured subband coders, Proc. IEEE Int. Conf. , Piscataway, NJ: IEEE Press, 1984. 31. A. Habibi, Comparison of nth-order DPCM encoder with linear transformation and block quantization techniques, IEEE Trans.

A. Croisier, D. Esteban, and C. Galand, Perfect channel splitting by use of interpolation/decimation techniques, Proc. Int. Conf. Inf. Sci. , Piscataway, NJ: IEEE Press, 1976. 29. J. D. Johnson, A filter family designed for use in quadrature mirror filter banks, Proc. IEEE Int. Conf. , Piscataway, NJ: IEEE Press, 1980, pp. 291–294. 696 DATA-FLOW AND MULTITHREADED ARCHITECTURES 30. M. J. T. Smith and T. P. Barnwell III, A procedure for designing exact reconstruction filter banks for tree structured subband coders, Proc.

Here the form of dependence on the parameter and the set ⌰ are assumed to be known. The problem of estimation of an unknown parameter ␪ or of the value g(␪) of a function g at the point ␪ consists of constructing a function ␪ˆ (X) from the observations, which gives a sufficiently good approximation of ␪ (or of g(␪)). A commonly accepted approach to comparing estimators, resulting from A. Wald’s contributions, is as follows: consider a quadratic loss function q(␪ˆ (X) Ϫ ␪) (or, more generally, a nonnegative function w(␪ˆ (X), ␪)), and given two estimators ␪ˆ 1(X) and ␪ˆ 1(X), the estimator for which the expected loss (risk) Eq(␪ˆ i(X) Ϫ ␪), i ϭ 1, 2 is the smallest is called the better, with respect to the quadratic loss function q (or to w).

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