Radial basis function network
Radial basis function network a fully connected feedforward network with a single hidden layer of neurons each of which computes a nonlinear decreasing function of the distance between its received input and a “center point.” This function is generally bell-shaped and has a different center point for each neuron. The center points and the widths of the bell shapes are learned from training data. The input weights usually have fixed values and may be prescribed on the basis of prior knowledge. The outputs have linear characteristics, and their weights are computed during training.
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Author of the text: Ed. P.A. Laplante Boca Raton: CRC Press LLC, 2000
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