By Topic

A synchronization based algorithm for discovering ellipsoidal clusters in large datasets

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
H. Frigui ; Dept. of Electr. & Comput. Eng., Univ. of Memphis, TN, USA ; M. B. H. Rhouma

This paper introduces a new scalable approach to clustering based on the synchronization of pulse-coupled oscillators. Each data point is represented by an integrate-and-fire oscillator and the interaction between oscillators is defined according to the relative similarity between the points. The set of oscillators self-organizes into stable phase-locked subgroups. Our approach proceeds by loading only a subset of the data and allowing it to self-organize. Groups of synchronized oscillators are then summarized and purged from memory. We show that our method is robust, scales linearly and can determine the number of clusters. The proposed approach is empirically evaluated with several synthetic data sets and is used to segment large color images

Published in:

Data Mining, 2001. ICDM 2001, Proceedings IEEE International Conference on

Date of Conference:

2001