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- Publications
- Influence

On cluster validity for the fuzzy c-means model

Many functionals have been proposed for validation of partitions of object data produced by the fuzzy c-means (FCM) clustering algorithm. We examine the role a subtle but important parameter-the… Expand

A possibilistic fuzzy c-means clustering algorithm

- N. Pal, K. Pal, J. Keller, J. Bezdek
- Mathematics, Computer Science
- IEEE Transactions on Fuzzy Systems
- 1 August 2005

In 1997, we proposed the fuzzy-possibilistic c-means (FPCM) model and algorithm that generated both membership and typicality values when clustering unlabeled data. FPCM constrains the typicality… Expand

Some new indexes of cluster validity

We review two clustering algorithms (hard c-means and single linkage) and three indexes of crisp cluster validity (Hubert's statistics, the Davies-Bouldin index, and Dunn's index). We illustrate two… Expand

A review on image segmentation techniques

Many image segmentation techniques are available in the literature. Some of these techniques use only the gray level histogram, some use spatial details while others use fuzzy set theoretic… Expand

Some new information measures for fuzzy sets

- D. Bhandari, N. Pal
- Mathematics, Computer Science
- Inf. Sci.
- 15 January 1993

Abstract After reviewing some existing measures for fuzzy sets, we introduce a new informative measure for discrimination between two fuzzy sets. This discriminating measure reduces to the… Expand

A robust self-tuning scheme for PI- and PD-type fuzzy controllers

Proposes a simple but robust model independent self-tuning scheme for fuzzy logic controllers (FLCs). Here, the output scaling factor (SF) is adjusted online by fuzzy rules according to the current… Expand

A mixed c-means clustering model

We justify the need for computing both membership and typicality values when clustering unlabeled data. Then we propose a new model called fuzzy-possibilistic c-means (FPCM). Unlike the fuzzy and… Expand

Fuzzy Kohonen clustering networks

- Eric Chen-Kuo Tsao, J. Bezdek, N. Pal
- Computer Science
- Pattern Recognit.
- 1 May 1994

Kohonen networks are well known for cluster analysis (unsupervised learning). This class of algorithms is a set of heuristic procedures that suffers from several major problems (e.g. neither… Expand

Two soft relatives of learning vector quantization

Abstract Learning vector quantization often requires extensive experimentation with the learning rate distribution and update neighborhood used during iteration towards good prototypes. A single… Expand

Measuring fuzzy uncertainty

First, this paper reviews several well known measures of fuzziness for discrete fuzzy sets. Then new multiplicative and additive classes are defined. We show that each class satisfies five well-known… Expand