Results 211 to 220 of about 1,229,548 (261)
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Order statistics on a hypercube
Information Processing Letters, 1988We consider an order statistics problem, a variant of the selection problem. We present an optimal parallel algorithm to find the highest k elements out of a set of n totally ordered (but not sorted) elements. This algorithm runs on a hypercube multiprocessor in O(n/p) time (p is the number of processors) using up to O(n1-θ) processors ...
Sharat Chandran, Azriel Rosenfeld
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Distribution of concomitants of order statistics and their order statistics
Journal of Statistical Planning and Inference, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
He, Qinying, Nagaraja, H. N.
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The entropy of ordered sequences and order statistics
IEEE Transactions on Information Theory, 1990The entropy of a sequence of random variables under order restrictions is examined. A theorem that shows the amount of entropy reduction when the sequence is ordered is presented. Upper and lower bounds to the entropy reduction and conditions under which they are achieved are derived.
Kon Max Wong, Shuang Chen
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International Journal of Intelligent Systems, 1999
Summary: Robust signal processing algorithms rely on integer ordered statistics. This means that such algorithms cannot be used in a fuzzy environment where variables have fuzzy ranks. We show how to calculate the \(k\)th order statistic for a set of arguments with fuzzy rank and thereby use classical robust signal processing algorithms in a fuzzy ...
Paul A. Schaefer +2 more
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Summary: Robust signal processing algorithms rely on integer ordered statistics. This means that such algorithms cannot be used in a fuzzy environment where variables have fuzzy ranks. We show how to calculate the \(k\)th order statistic for a set of arguments with fuzzy rank and thereby use classical robust signal processing algorithms in a fuzzy ...
Paul A. Schaefer +2 more
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Ordering distributions by scaled order statistics
Zeitschrift f�r Operations Research, 1987Motivated by applications in reliability theory, we define a preordering \((X_ 1,...,X_ n)\lesssim^{(k)}(Y_ 1,...,Y_ n)\) of nonnegative random vectors by requiring the k-th order statistic of \(a_ 1X_ 1,...,a_ nX_ n\) to be stochastically smaller than the k-th order statistic of \(a_ 1Y_ 1,...,a_ nY_ n\) for all choices of \(a_ i>0\), \(i=1,2,...,n\).
SCARSINI, MARCO, M. Shaked
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Proceedings of 1st International Conference on Image Processing, 1996
Filter banks play a major role in multirate signal processing where these have been successfully used in a variety of applications. In the past, filter banks have been developed within the framework of linear filters. It is well known, however, that linear filters may have less than satisfactory performance whenever the underlying processes are non ...
Gonzalo R. Arce, Mu Tian
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Filter banks play a major role in multirate signal processing where these have been successfully used in a variety of applications. In the past, filter banks have been developed within the framework of linear filters. It is well known, however, that linear filters may have less than satisfactory performance whenever the underlying processes are non ...
Gonzalo R. Arce, Mu Tian
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On the dependence structure of order statistics and concomitants of order statistics
Journal of Statistical Planning and Inference, 1990zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kim, S. H., David, H. A.
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Completeness of Order Statistics
Canadian Journal of Mathematics, 19541. Introduction. Under the non-parametric assumption that a set of observations is a sample from an absolutely continuous distribution, the order statistics are known to form a complete sufficient statistic. It is proved in this note that it suffices to have the class of uniform distributions over finite numbers of intervals or the class of uniform ...
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Order Statistics and Nonparametric Statistics.
1978Abstract : The research reported falls under the headings: (a) order statistics; (b) competing risks; (c) nonparametric statistics, and (d) cyclic designs. (a) Concomitants of order statistics were introduced and studied as a class, and applications in selection and double sampling provided. The robustness of various estimators of location and scale in
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