Hardware implementation of intelligent systems
Hardware implementation of intelligent systems
A digital fuzzy processor for fuzzy-rule-based systems
Hardware implementation of intelligent systems
Hybrid multimode/multirate CS-ACELP speech coding for adaptive voice over IP
Speech Communication
Intrastandard Hybrid Speech Coding for Adaptive IP Telephony
QoS-IP '01 Proceedings of the International Workshop on Quality of Service in Multiservice IP Networks
Evolutionary Subsethood Product Fuzzy Neural Network
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Fuzzy modelling through logic optimization
International Journal of Approximate Reasoning
A coevolutionary genetic algorithm using fuzzy clustering
Intelligent Data Analysis
Optimization of fuzzy partitions for inductive reasoning using genetic algorithms
International Journal of Systems Science
Holonic multi-agent system model for fuzzy automatic speech / speaker recognition
KES-AMSTA'08 Proceedings of the 2nd KES International conference on Agent and multi-agent systems: technologies and applications
A multi-objective neuro-evolutionary algorithm to obtain interpretable fuzzy models
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Design of t–s fuzzy classifier via linear matrix inequality approach
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Evolutionary computation and its applications in neural and fuzzy systems
Applied Computational Intelligence and Soft Computing
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The author has developed a novel approach to fuzzy modeling from input-output data. Using the basic techniques of soft computing, the method allows supervised approximation of multi-input multi-output (MIMO) systems. Typically, a small number of rules are produced. The learning capacity of FuGeNeSys is considerable, as is shown by the numerous applications developed. The paper gives a significant example of how the fuzzy models developed are generally better than those to be found in literature as concerns simplicity and both approximation and classification capabilities