1978 - IEEE Fellow For contributions to system identification, state estimation, and their application to aerospace technology.
His scientific interests lie mostly in Fuzzy set, Fuzzy logic, Algorithm, Fuzzy number and Artificial intelligence. The study incorporates disciplines such as Data mining and Interval in addition to Fuzzy set. The Fuzzy logic study combines topics in areas such as Computational complexity theory, Control theory and Arithmetic.
His Algorithm research integrates issues from Convergence, Centroid and Mathematical optimization. His biological study spans a wide range of topics, including Fuzzy set operations and Fuzzy classification. His Artificial intelligence research includes themes of Machine learning and Pattern recognition.
His primary scientific interests are in Fuzzy set, Algorithm, Artificial intelligence, Fuzzy logic and Fuzzy number. In his study, Type is strongly linked to Interval, which falls under the umbrella field of Fuzzy set. His Algorithm research includes elements of Cumulant, Mathematical optimization and Signal processing.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Machine learning and Pattern recognition. His studies deal with areas such as Discrete mathematics and Control system, Control theory as well as Fuzzy logic. Jerry M. Mendel interconnects Fuzzy set operations and Fuzzy classification in the investigation of issues within Fuzzy number.
Jerry M. Mendel mainly investigates Fuzzy set, Artificial intelligence, Interval, Fuzzy logic and Algorithm. The concepts of his Fuzzy set study are interwoven with issues in Word and Data mining. Jerry M. Mendel works mostly in the field of Artificial intelligence, limiting it down to topics relating to Machine learning and, in certain cases, Computational linguistics.
His research in Fuzzy logic focuses on subjects like Control theory, which are connected to Control engineering. His Algorithm study combines topics from a wide range of disciplines, such as Convergence and Centroid. His Fuzzy number research incorporates themes from Fuzzy set operations and Fuzzy classification.
Fuzzy set, Interval, Fuzzy logic, Algorithm and Artificial intelligence are his primary areas of study. His work on Fuzzy set deals in particular with Fuzzy number and Type-2 fuzzy sets and systems. His Fuzzy number study also includes
His research in Fuzzy logic intersects with topics in Control system, Control theory and Weighted geometric mean. His Algorithm research is multidisciplinary, incorporating perspectives in Convergence and Centroid. In general Artificial intelligence, his work in Fuzzy control system, Similarity measure, Fuzzy electronics and Outlier is often linked to Parallel coordinates linking many areas of study.
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Generating fuzzy rules by learning from examples
L.-X. Wang;J.M. Mendel.
systems man and cybernetics (1992)
Fuzzy basis functions, universal approximation, and orthogonal least-squares learning
L.-X. Wang;J.M. Mendel.
IEEE Transactions on Neural Networks (1992)
Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions
Jerry M. Mendel.
Fuzzy logic systems for engineering: a tutorial
Proceedings of the IEEE (1995)
Type-2 fuzzy sets made simple
J.M. Mendel;R.I.B. John.
IEEE Transactions on Fuzzy Systems (2002)
Tutorial on higher-order statistics (spectra) in signal processing and system theory: theoretical results and some applications
Proceedings of the IEEE (1991)
Interval Type-2 Fuzzy Logic Systems Made Simple
J.M. Mendel;R.I. John;F. Liu.
IEEE Transactions on Fuzzy Systems (2006)
Interval type-2 fuzzy logic systems: theory and design
Qilian Liang;J.M. Mendel.
IEEE Transactions on Fuzzy Systems (2000)
Type-2 fuzzy logic systems
N.N. Karnik;J.M. Mendel;Qilian Liang.
IEEE Transactions on Fuzzy Systems (1999)
Centroid of a type-2 fuzzy set
Nilesh N. Karnik;Jerry M. Mendel.
Information Sciences (2001)
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