Deadzone compensation based on constrained RBF neural network
Two neural networks are used for the compensation of a deadzone. A radial basis function (RBF) neural network is used for the identification of the parameters. Then the RBF network acts as a single layer neural network and is trained based on the gradient descent technique. The result is used to train the other neural network for the inverse compensation of the deadzone.
scientific article; zbMATH DE number 2134374