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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...

An automatic hybrid method for retinal blood vessel extraction

Yong Yang, Shuying Huang, Nini Rao (2008)

International Journal of Applied Mathematics and Computer Science

The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper presents a novel hybrid automatic approach for the extraction of retinal image vessels. The method consists in the application of mathematical morphology and a fuzzy clustering algorithm followed by a purification procedure. In mathematical morphology, the retinal image is smoothed and strengthened so that the blood vessels are enhanced and the background information...

Análisis bayesiano de problemas de decisión con valoración difusa de las consecuencias

A. Gil Álvarez, María Ángeles Gil Álvarez (1998)

Revista de la Real Academia de Ciencias Exactas Físicas y Naturales

En este trabajo se presenta un modelo matemático general y operativo para los problemas de decisión unietápicos cuyas consecuencias se cuantifican mediante números difusos. Ese modelo va a permitir establecer los fundamentos de las utilidades difusas mediante un desarrollo axiomático, y generalizar las formas normal y extensiva del análisis bayesiano dando condiciones para la equivalencia de las mismas. Se examinará también la particularización del análisis bayesiano en forma extensiva a la estimación...

Fuzzy clustering of spatial binary data

Mô Dang, Gérard Govaert (1998)


An iterative fuzzy clustering method is proposed to partition a set of multivariate binary observation vectors located at neighboring geographic sites. The method described here applies in a binary setup a recently proposed algorithm, called Neighborhood EM, which seeks a partition that is both well clustered in the feature space and spatially regular [AmbroiseNEM1996]. This approach is derived from the EM algorithm applied to mixture models [Dempster1977], viewed as an alternate optimization method...

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