The problem is said to be tractable if there exist constants c, α, β independent of q (but possibly dependent on μ and F) such that En(F , μ) ≤ cqαn−β. We explore different regions (including manifolds), function classes, and measures for which this problem is tractable. Our results include tractability theorems for integration with respect to non-tensor product measures, and over unbounded and...

In this paper, a new approach for the compensation of unknown periodic disturbances by means of a neural network is presented. The neural controller supports the conventional controller by suppressing periodic disturbances. This is done by online learning in order to adapt to different operating conditions and to time varying unknown disturbances. The neural network learns an optimal compensati...

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 tra...

The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Radial basis function neural networks (RBFNNs), which is a relatively new class of neural networks, have been investigated for their applicability for prediction of performance and emission characteristics of a diesel engine fuelled with waste cooking oil (WCO). The RBF network...

In this paper, a supervised technique for training radial basis function (RBF) neural network classifiers is proposed. Such a technique, unlike traditional ones, considers the class memberships of training samples to select the centers and widths of the kernel functions associated with the hidden neurons of an RBF network. The result is twofold: a significant reduction in the overall classifica...

Among the neural network models RBF(Radial Basis Function) network seems to be quite effective for a pattern recognition task such as handwritten numeral recognition since it is extremely flexible to accommodate various and minute variations in data. Recently we obtained a good recognition rate for handwritten numerals by using an RBF network. In this paper we show how to design an RBF network ...

A connectionist model made up of a combination of RBF networks is proposed the model decomposes multivalued dependencies into local single valued functions theory and applications are presented

On page 8 of the paper (page 3209 of the volume), in the seventh line of the second-to-last paragraph of section 5.