Neural Comput - A new clustering approach on the basis of dynamical neural field.

Tópicos

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Resumo

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.

Resumo Limpo

letter present new hierarch cluster approach base evolutionari process amari dynam neural field model dynam neural field theori provid theoret framework macroscop describ activ neuron ensembl base cluster approach essenti close neurophysiolog natur percept also comput stabl insensit nois flexibl tractabl data complex structur exampl given show feasibl

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