Dybowski, Richard (1998) ‘Classification of incomplete feature vectors by radial basis function networks’, Pattern Recognition Letters, 19(14), pp. 1257-1264.
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The paper describes the use of radial basis function neural networks with Gaussian basis functions to classify incomplete feature vectors. The method uses the fact that any marginal distribution of a Gaussian distribution can be determined from the mean vector and covariance matrix of the joint distribution.
|Divisions:||Schools > Architecture Computing and Engineering, School of|
|Additional Information:||Citation: Dybowski R. (1998) "Classification of incomplete feature vectors by radial basis function networks". Pattern Recognition Letters, 19 (14) 1257-1264.|
|Date Deposited:||02 Nov 2009 14:39|
|Last Modified:||27 Sep 2012 11:58|
|Depositing User:||Stephen Grace|