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A posteriori disclosure risk measure for tabular data based on conditional entropy.

Anna Oganian, Josep Domingo-Ferrer (2003)

SORT

Statistical database protection, also known as Statistical Disclosure Control (SDC), is a part of information security which tries to prevent published statistical information (tables, individual records) from disclosing the contribution of specific respondents. This paper deals with the assessment of the disclosure risk associated to the release of tabular data. So-called sensitivity rules are currently being used to measure the disclosure risk for tables. This rules operate on an a priori basis:...

A practical application of kernel-based fuzzy discriminant analysis

Jian-Qiang Gao, Li-Ya Fan, Li Li, Li-Zhong Xu (2013)

International Journal of Applied Mathematics and Computer Science

A novel method for feature extraction and recognition called Kernel Fuzzy Discriminant Analysis (KFDA) is proposed in this paper to deal with recognition problems, e.g., for images. The KFDA method is obtained by combining the advantages of fuzzy methods and a kernel trick. Based on the orthogonal-triangular decomposition of a matrix and Singular Value Decomposition (SVD), two different variants, KFDA/QR and KFDA/SVD, of KFDA are obtained. In the proposed method, the membership degree is incorporated...

A probability density function estimation using F-transform

Michal Holčapek, Tomaš Tichý (2010)

Kybernetika

The aim of this paper is to propose a new approach to probability density function (PDF) estimation which is based on the fuzzy transform (F-transform) introduced by Perfilieva in [10]. Firstly, a smoothing filter based on the combination of the discrete direct and continuous inverse F-transform is introduced and some of the basic properties are investigated. Next, an alternative approach to PDF estimation based on the proposed smoothing filter is established and compared with the most used method...

A procedure for ε-comparison of means of two normal distributions

Stanisław Jaworski, Wojciech Zieliński (2004)

Applicationes Mathematicae

For two normal distributions N(μ₁,σ²) and N(μ₂,σ²) the problem is to decide whether |μ₁-μ₂|≤ ε for a given ε. Two decision rules are given: maximin and bayesian for σ² known and unknown.

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