Radial basis functions for multivariable interpolation: a review
Algorithms for approximation
Neuro-Control and Its Applications
Neuro-Control and Its Applications
Real-Time Identification of Nonlinear Time-Varying Systems Using Radial Basis Function Network
Cybernetics and Systems Analysis
Adaptive Control of Multidimensional Nonlinear Objects on the Basis of Radial-Basis Networks
Cybernetics and Systems Analysis
A new structure adaptation algorithm for RBF networks and its application
Neural Computing and Applications
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Fast learning in networks of locally-tuned processing units
Neural Computation
An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Shape-adaptive radial basis functions
IEEE Transactions on Neural Networks
Approximation of nonlinear systems with radial basis function neural networks
IEEE Transactions on Neural Networks
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An approach to the development of a neurocontroller for controlling nonlinear dynamical objects on the basis of radial-basis function neural networks is considered. Piecewise-linear approximation of Gaussian basis functions is proposed to simplify the solution of the problem being considered. Simulation results show that the method allows one to reduce the time of construction of an object model and calculation of its control signal.