Radial basis functions for multivariable interpolation: a review
Algorithms for approximation
Fast learning in networks of locally-tuned processing units
Neural Computation
Gaussian networks for direct adaptive control
IEEE Transactions on Neural Networks
| Hi-index | 0.98 |
The systematic storage in neural networks of prior information to be used in the design of various control subsystems is investigated. Assuming that the prior information is available in a certain form (namely, input/output data points and specifications between the data points), a particular neural network using Gaussian nonlinearities and a corresponding parameter design method are introduced. The proposed neural network addresses the issue of effectively using prior information, and its use is illustrated in an implementation of a control law scheduler.