Journal of Algorithms - Analysis of algorithms
Collaborative fuzzy clustering
Pattern Recognition Letters
Towards a robust fuzzy clustering
Fuzzy Sets and Systems - Data analysis
Clustering: A neural network approach
Neural Networks
A time-domain-constrained fuzzy clustering method and its application to signal analysis
Fuzzy Sets and Systems
Robust fuzzy clustering using adaptive fuzzy meridians
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part I
Hybrid fuzzy clustering using LP norms
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
Alternative fuzzy clustering algorithms with l1-norm and covariance matrix
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
The fuzzy mega-cluster: robustifying FCM by scaling down memberships
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Robust fuzzy clustering with fuzzy data
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
Segmentation of images with separating layers by fuzzy c-means and convex optimization
Journal of Visual Communication and Image Representation
Fuzzy clustering of intuitionistic fuzzy data
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Computer assisted location of the lower limb mechanical axis
ITIB'12 Proceedings of the Third international conference on Information Technologies in Biomedicine
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The median and the median absolute deviation (MAD) are robust statistics based on order statistics. Order statistics are extended to fuzzy sets to define a fuzzy median and a fuzzy MAD. The fuzzy c-means (FCM) clustering algorithm is defined for any p-norm (pFCM), including the l1-norm (1FCM), The 1FCM clustering algorithm is implemented via the alternating optimization (AO) method and the clustering centers are shown to be the fuzzy median. The resulting AO-1FCM clustering algorithm is called the fuzzy c-medians (FCMED) clustering algorithm. An example illustrates the robustness of the FCMED