Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/5312
Author(s): Nunes, Luís
Almeida, Luís B.
Langlois, Thibault
Date: 11-Jul-2013
Title: Interpolation Networks
Pages: 1750-1754
Event title: International Conference on Neural Networks (ICNN96)
Keywords: Interpolation Networks
Radial Basis Functions
initialisation by prototypes
Neural Networks
Abstract: This paper introduces a new type of network based on local response units, the ‘Intelpolation Networh’ (INS).U nder certain conditions this network is an interpolator. Its formulation allows a type of initialisation by prototypes that will set the net in a good initial starting point for the subsequent supervised learning process. These networks can be seen as a type of ‘Radial Basis Functions Network’ (RBFN) [Moody88]. However, their basis functions are essentially inverse squared distances instead of Gaussian functions. A brief description of the origin and motivation of INS is made in the first section, followed by the description of the first experiments with these networks.
Peerreviewed: Sim
Access type: Restricted Access
Appears in Collections:CTI-CRI - Comunicações a conferências internacionais

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