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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Journal ArticleDOI
On applying spatial constraints in fuzzy image clustering using a fuzzy rule-based system
Y.A. Tolias,Stavros M. Panas +1 more
TL;DR: The results of the proposed rule-based neighborhood enhancement (RB-NE) system are compared to well-known segmentation algorithms using stochastic field modeling and are found to be of comparable quality, while being of lower computational complexity.
Journal ArticleDOI
Identification of complex systems based on neural and Takagi-Sugeno fuzzy model
Dragan Kukolj,Emil Levi +1 more
TL;DR: The proposed method generates a Takagi-Sugeno fuzzy model, characterized with transparency, high accuracy and a small number of rules, which uses numerical data as a starting point for neuro-fuzzy identification.
Journal ArticleDOI
The nearest subclass classifier: a compromise between the nearest mean and nearest neighbor classifier
TL;DR: The nearest subclass classifier (NSC), which is a classification algorithm that unifies the flexibility of the nearest neighbor classifier with the robustness ofThe nearest mean classifier, is presented, which belongs to the class of prototype-based classifiers.
Journal ArticleDOI
An overview on fault diagnosis and nature-inspired optimal control of industrial process applications
TL;DR: The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system and nature-inspired optimal control.
Journal ArticleDOI
A fuzzy rule-based system for epileptic seizure detection in intracranial EEG.
TL;DR: The fuzzy rule-based seizure detection system enabled us to deal with imprecise boundaries between interictal and ictal IEEG patterns and may serve as a good seizure detection tool with high sensitivity and low false detection rate for monitoring long-term IEEGs.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Book
Introduction to Statistical Pattern Recognition
TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
A fuzzy relative of the isodata process and its use in detecting compact well-separated clusters
TL;DR: In this paper, two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space, and the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the LSE criterion function.