Daniel@0: Daniel@0: Daniel@0: Daniel@0: Netlab Reference Manual rbfbkp Daniel@0: Daniel@0: Daniel@0: Daniel@0:

rbfbkp Daniel@0:

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Daniel@0: Purpose Daniel@0:

Daniel@0: Backpropagate gradient of error function for RBF network. Daniel@0: Daniel@0:

Daniel@0: Synopsis Daniel@0:

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Daniel@0: g = rbfbkp(net, x, z, n2, deltas)

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Daniel@0: Description Daniel@0:

Daniel@0: g = rbfbkp(net, x, z, n2, deltas) takes a network data structure Daniel@0: net together with a matrix x of input vectors, a matrix Daniel@0: z of hidden unit activations, a matrix n2 of the squared Daniel@0: distances between centres and inputs, and a matrix deltas of the Daniel@0: gradient of the error function with respect to the values of the Daniel@0: output units (i.e. the summed inputs to the output units, before the Daniel@0: activation function is applied). The return value is the gradient Daniel@0: g of the error function with respect to the network Daniel@0: weights. Each row of x corresponds to one input vector. Daniel@0: Daniel@0:

This function is provided so that the common backpropagation algorithm Daniel@0: can be used by RBF network models to compute Daniel@0: gradients for the output values (in rbfderiv) as well as standard error Daniel@0: functions. Daniel@0: Daniel@0:

Daniel@0: See Also Daniel@0:

Daniel@0: rbf, rbfgrad, rbfderiv

Daniel@0: Pages: Daniel@0: Index Daniel@0:

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