Generalizations of Fuzzy Information Measures / by Anshu Ohlan, Ramphul Ohlan
By: Ohlan, Anshu.
Contributor(s): SpringerLink (Online service) | Ohlan, Ramphul.
Material type: 
E-bookPublisher: Cham : Springer International Publishing, 2016Description: 1 recurso en línea (IX, 146 páginas) : 7 ilustraciones.ISBN: 9783319459288.Subject: Reconocimiento de formas | BiometríaDDC classification: 006.4 Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds | |
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | QA248.5 O353 2016 EB (Browse shelf(Opens below)) | .i11598281 | Acceso electrónico | eBOOK .i11598281 |
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Fundamentals of Fuzzy Information Measures -- Parametric Generalized R?Norm Fuzzy Information and Divergence Measures -- Parametric Generalized R?Norm Fuzzy Information and Divergence Measures -- Parametric Generalized Exponential Fuzzy Divergence Measure and Strategic Decision Making -- Sequence and Application of Inequalities Among Fuzzy Mean Difference Divergence Measures in Pattern Recognition -- Applications of Generalized Fuzzy Divergence Measure in Multi-criteria Decision Making and Pattern Recognition -- Generalized Hellinger�s Fuzzy Divergence Measure and Its Applications -- Intuitionistic Fuzzy Exponential Divergence and Multi-Attribute Decision Making.
This book develops applications of novel generalizations of fuzzy information measures in the field of pattern recognition, medical diagnosis, multi-criteria and multi-attribute decision making and suitability in linguistic variables. The focus of this presentation lies on introducing consistently strong and efficient generalizations of information and information-theoretic divergence measures in fuzzy and intuitionistic fuzzy environment covering different practical examples. The target audience comprises primarily researchers and practitioners in the involved fields but the book may also be beneficial for graduate students.
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