Classification of incomplete feature vectors by radial basis function networks
نویسنده
چکیده
The paper describes the use of radial basis function neural networks with Gaussian basis functions to classify incomplete feature vectors. The method exploits the fact that any marginal distribution of a defined Gaussian joint distribution can be determined from the mean vector and covariance matrix of the joint distribution. The method is discussed in the context of complete and incomplete training sets.
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ورودعنوان ژورنال:
- Pattern Recognition Letters
دوره 19 شماره
صفحات -
تاریخ انتشار 1998