Radial Basis Function Network
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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. A radial basis function network is an artificial neural network that uses radial basis functions as activation functions. It is a linear combination of radial basis functions. They are used in function approximation, time series prediction, and control. In a RBF network there are three types of parameters that need to be chosen to adapt the network for a particular task: the center vectors mathbf c_i, the output weights wi, and the RBF width parameters i. In the seque...
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. A radial basis function network is an artificial neural network that uses radial basis functions as activation functions. It is a linear combination of radial basis functions. They are used in function approximation, time series prediction, and control. In a RBF network there are three types of parameters that need to be chosen to adapt the network for a particular task: the center vectors mathbf c_i, the output weights wi, and the RBF width parameters i. In the sequential training of the weights are updated at each time step as data streams in.
