in this paper, the geometric distribution is considered. the means, variances, and covariances of its order statistics are derived. the fisher information in any set of order statistics in any distribution can be represented as a sum of fisher information in at most two order statistics. it is shown that, for the geometric distribution, it can be further simplified to a sum of fisher informatio...

‎Recently‎, ‎a new distribution‎, ‎named as extended generalized exponential distribution‎, ‎has been introduced by Kundu and Gupta (2011). ‎In this paper‎, ‎we consider the extended generalized exponential distribution with known shape parameters α and β. ‎At first‎, ‎the exact expressions for marginal and product moments of o...

For automatic speech recognition, endpoint detection is required to isolate the speech of interest so as to be able to create a speech pattern or template. The process of separating the speech segments of an utterance from the nonspeech segments obtained during the recording process is called endpoint detection. In this paper, we present new endpoint detection algorithm based on high order stat...

Recent studies show that aggregating local descriptors into super vector yields effective representation for retrieval and classification tasks. A popular method along this line is vector of locally aggregated descriptors (VLAD), which aggregates the residuals between descriptors and visual words. However, original VLAD ignores high-order statistics of local descriptors and its dictionary may n...

Results are presented for a simple conditional-moments method that directly measures high-order statistics of natural images. In four estimation tasks significant increases in performance are obtained in comparison to traditional methods. OCIS codes: (100.0100) Image processing; (110.0110) Imaging systems; (330.0330) Vision, color, and visual optics

The high-order statistics (moments and cumulants of order higher than two) have been widely applied in several fields, specially in problems where it is conjectured a lack of Gaussianity and/or non-linearity. Since the INteger-valued AutoRegressive, INAR, models are non-Gaussian, the high-order statistics can provide additional information that allows a better characterization of these processe...

In this paper, we derive the exact analytical expressions for the Shannon entropy of generalized orderstatistics from Pareto-type and related distributions.

The dual generalized order statistics is a unified model which contains the well known decreasingly ordered random data such as (reversed ordered) order statistics and lower record values. In the present paper, some characterization results on the power function distribution based on the properties of dual generalized order statistics are provided. The results are proved without any rest...