Modular neural networks and type-2 fuzzy systems for pattern recognition / Patricia Melin.

Author/creator Melin, Patricia, 1962-
Format Electronic
Publication InfoBerlin : Springer-Verlag,
Descriptionx, 214 p. : ill. (some col.) ; 24 cm.
Supplemental ContentFull text available from SpringerLINK Studies in Computational Intelligence Contemporary (1997-present)
Subjects

SeriesStudies in computational intelligence, 1860-949X ; v. 389
Studies in computational intelligence v. 389. ^A766031
Contents 1. Introduction to type-2 fuzzy logic in neural pattern recognition -- 2. Type-1 and Type-2 fuzzy inference systems for images edge detection -- 3. Type-2 fuzzy logic for improving training data and response integration in modular neural networks -- 4. Method for response integration in modular neural networks using type-2 fuzzy logic -- 5. Modular neural networks for person recognition using the contour segmentation of the human iris -- 6. Modular neural networks for human recognition from ear images compressed using wavelets -- 7. Signature recognition with a hybrid approach combining modular neural networks and fuzzy logic for response integration -- 8. Interval type-2 fuzzy logic for module relevance estimation in sugeno response integration of modular neural networks -- 9. Optimization of fuzzy response integrators in modular neural networks with hierarchical genetic algorithms -- 10. Modular neural network with fuzzy response integration and its optimization using genetic algorithms for human recognition based on iris, ear and voice biometrics -- 11. A comparative study of type-2 fuzzy system optimization based on parameter uncertainty of membership functions -- 12. Neural network optimization for the recognition of persons using the iris biometric measure -- 13. Optimization of neural networks for the accurate identification of persons by images of the human ear as biometric measure.
Bibliography noteIncludes bibliographical references (p. [205]-211) and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2011939329
ISBN9783642241383 (alk. paper)
ISBN3642241387 (alk. paper)
ISBN9783642241390 (e-ISBN)