Structure identification of fuzzy model
Fuzzy Sets and Systems
Introduction to artificial neural systems
Introduction to artificial neural systems
Classification by fuzzy integral: performance and tests
Fuzzy Sets and Systems - Special issue on fuzzy methods for computer vision and pattern recognition
Aggregation operators and fuzzy systems modeling
Fuzzy Sets and Systems
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A new type of nonlinear integrals and the computational algorithm
Fuzzy Sets and Systems
On the representation of Choquet integrals of set-valued functions, and null sets
Fuzzy Sets and Systems
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fundamentals of Uncertainty Calculi with Applications to Fuzzy Inference
Fuzzy Measures and Integrals: Theory and Applications
Fuzzy Measures and Integrals: Theory and Applications
Control and identification of non-linear systems affected by noise using wavelet network
Second international workshop on Intelligent systems design and application
IEEE Transactions on Pattern Analysis and Machine Intelligence
New fuzzy wavelet neural networks for system identification and control
Applied Soft Computing
Off-line signature verification and forgery detection using fuzzy modeling
Pattern Recognition
Choquet fuzzy integral-based hierarchical networks for decision analysis
IEEE Transactions on Fuzzy Systems
Q-measures: an efficient extension of the Sugeno λ-measure
IEEE Transactions on Fuzzy Systems
Structure identification of generalized adaptive neuro-fuzzy inference systems
IEEE Transactions on Fuzzy Systems
A new approach to fuzzy-neural system modeling
IEEE Transactions on Fuzzy Systems
A fuzzy-logic-based approach to qualitative modeling
IEEE Transactions on Fuzzy Systems
LMS learning algorithms: misconceptions and new results on converence
IEEE Transactions on Neural Networks
Identification and control of dynamical systems using neural networks
IEEE Transactions on Neural Networks
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For dealing with adjacent input fuzzy sets having overlapping information, non-additive fuzzy rules are formulated by defining their consequent as a function of fuzzy measures, i.e., a simple form of Choquet integral. The fuzzy measures aggregate the information from the overlapping fuzzy sets using the λ-measure. The defuzzified output of these rules is also in the general form of the Choquet fuzzy integral. The underlying non-additive fuzzy model is investigated for both identification and control of non-linear systems. The identification of this fuzzy model involves the strength of the rules as the known input functions and fuzzy densities required to compute fuzzy measures as the unknown functions to be estimated. The use of q-measure provides a more flexible and powerful way of simplifying the computation of λ-measure used to take account of interaction between the fuzzy sets. This model has been successfully applied to the real life problem of verifying the authenticity of offline signatures.