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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Journal ArticleDOI
Automatic image pixel clustering with an improved differential evolution
Swagatam Das,Amit Konar +1 more
TL;DR: Extensive performance comparison among the new method, a recently developed genetic-fuzzy clustering technique and the classical fuzzy c-means algorithm over a test suite comprising ordinary grayscale images and remote sensing satellite images reveals the superiority of the proposed technique in terms of speed, accuracy and robustness.
Journal ArticleDOI
Hybrid intelligent systems for time series prediction using neural networks, fuzzy logic, and fractal theory
Oscar Castillo,Patricia Melin +1 more
TL;DR: A new method for the estimation of the fractal dimension of a geometrical object using fuzzy logic techniques and it is proposed that this dimension incorporates the concept of a fuzzy set, which can be considered a weaker definition (but more realistic) of the Fractal dimension.
Journal ArticleDOI
Clustering of resting state networks
Megan H. Lee,Carl D. Hacker,Abraham Z. Snyder,Maurizio Corbetta,Dongyang Zhang,Eric C. Leuthardt,Joshua S. Shimony +6 more
TL;DR: The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results, which reinforces the observation that resting state Networks are hierarchically organized.
Journal ArticleDOI
Automatic clustering using nature-inspired metaheuristics
TL;DR: An up-to-date review of all major nature-inspired metaheuristic algorithms used thus far for automatic clustering, with a strong tendency in using multiobjective and hybrid algorithms to address non-linearly separable problems.
Journal ArticleDOI
A simple and fast method to determine the parameters for fuzzy c–means cluster analysis
Veit Schwämmle,Ole N. Jensen +1 more
TL;DR: This result speaks strongly against using a predefined fuzzifier as typically done in many previous studies, and proposes a functional relationship determining the fuzzifier directly.
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.