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Pattern Recognition with Fuzzy Objective Function Algorithms

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Citations
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Journal ArticleDOI

A fuzzy clustering neural network architecture for multifunction upper-limb prosthesis

TL;DR: The results suggest that FCNN can generalize better than other NN algorithms and help the user learn better and faster and has the potential of being very efficient in real-time applications.
Journal ArticleDOI

On a class of fuzzy c -numbers clustering procedures for fuzzy data

TL;DR: New types of fuzzy clustering procedures in dealing with fuzzy data are derived, called fuzzy c-numbers (FCN) clusterings, which construct these FCNs for U-type, triangular, trapezoidal and normal fuzzy numbers.
Journal ArticleDOI

A fuzzy extension of the Rand index and other related indexes for clustering and classification assessment

TL;DR: A fuzzy extension of the Rand index is introduced, able to evaluate a fuzzy partition of a data set - provided by a fuzzy clustering algorithm or a classifier with fuzzy-like outputs - against a reference hard partition that encodes the actual (known) data classes.
Journal ArticleDOI

Hyperspectral image unsupervised classification by robust manifold matrix factorization

TL;DR: This work proposes a hyperspectral image unsupervised classification framework based on robust manifold matrix factorization and its out-of-sample extension and designs a novel Augmented Lagrangian Method (ALM) based procedure to seek the local optimal solution of the proposed optimization.
Journal ArticleDOI

Unsupervised learning of a finite mixture model based on the Dirichlet distribution and its application

TL;DR: An unsupervised algorithm for learning a finite mixture model from multivariate data based on the Dirichlet distribution, which offers high flexibility for modeling data.
References
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Journal ArticleDOI

Nearest neighbor pattern classification

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

J. C. Dunn
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.