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6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

August 2011, Vol. 23, No. 8, Pages 2032-2057
(doi: 10.1162/NECO_a_00153)
© 2011 Massachusetts Institute of Technology
A New Clustering Approach on the Basis of Dynamical Neural Field
Article PDF (2.72 MB)
Abstract

In this letter, we present a new hierarchical clustering approach based on the evolutionary process of Amari's dynamical neural field model. Dynamical neural field theory provides a theoretical framework macroscopically describing the activity of neuron ensemble. Based on it, our clustering approach is essentially close to the neurophysiological nature of perception. It is also computationally stable, insensitive to noise, flexible, and tractable for data with complex structure. Some examples are given to show the feasibility.