We will analyze the number of comparisons needed to solve the problem of sorting n distinct items into ascending order, and the related problem of selecting the kth smallest item from an unsorted list of n items. Section 1 examines mergesort, an algorithm with excellent worst case performance, and Section 2 examines quicksort, an algorithm with excellent average case performance. Section 3 cont...

Texture analysis is an important approach in textile quality control. Higher order statistics have been very useful in problems where non-Gaussianity, nonminimum phase, colored noise or nonlinearity is important. In this work, higher order statistical analysis is applied to texture defect detection problem. A neighborhood definition is proposed for cumulant lags of higher order statistics and i...

Sample estimates of moments and cumulants are known to be unstable in the presence of outliers. This problem is especially severe for higher order statistics, like kurtosis, which are used in algorithms for independent components analysis and projection pursuit. In this paper we propose robust generalizations of moments and cumulants that are more insensitive to outliers but at the same time re...

In this paper, assuming that (X, Y1, Y2)T has a trivariate normal distribution, we derive the exact joint distribution of ( X, Y(1), Y(2))^T, where Y(1) and Y(2) are order statistics arising from (Y1, Y2)T . We show that this joint distribution is a mixture of truncated trivariate normal distributions and then use this mixture representation to derive the best (nonlinear) predictiors of X...