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Pattern Recognition with Fuzzy Objective Function Algorithms
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Citations
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Swarm intelligence based fuzzy routing protocol for clustered wireless sensor networks
TL;DR: Simulation results show that SIF outperforms the existing clustering-based protocols in terms of generating balanced clusters and prolonging the network lifetime, and unlike other routing protocols which have been designed for a certain application scope, the main objective of the methodology is to prolong the network Lifetime based on the application specifications.
Journal ArticleDOI
A fuzzy logic classification scheme for selecting and blending satellite ocean color algorithms
TL;DR: An approach for selecting and blending bio-optical algorithms is demonstrated using an ocean color satellite image of the northwest Atlantic shelf based on a fuzzy logic classification scheme applied to the satellite-derived water-leaving radiance data and it is used to select and blend class-specific algorithms.
Journal ArticleDOI
Single-unit activity in cortical area MST associated with disparity-vergence eye movements: evidence for population coding.
TL;DR: Latency data suggest that this activity in MST occurs early enough to play an active role in the generation of vergence eye movements at short latencies, and hypothesize that the magnitude, direction, and time course of the initial vergence velocity responses associated with disparity steps applied to large patterns are all encoded in the summed activity of the disparity-sensitive cells in M ST.
Journal ArticleDOI
Fuzzy computing for data mining
K. Hirota,W. Pedrycz +1 more
TL;DR: This study introduces unsupervised learning (clustering) where optimization is supported by the linguistic granules of context, thereby giving rise to so-called context-sensitive fuzzy clustering.
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On voting-based consensus of cluster ensembles
Hanan Ayad,Mohamed S. Kamel +1 more
TL;DR: This paper shows that a recently introduced cumulative voting scheme is a special case corresponding to a linear regression method, and uses a randomized ensemble generation technique for extracting the consensus clustering from the aggregated ensemble representation and for estimating the number of clusters.
References
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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.