Daniel@0: Daniel@0: Daniel@0: Daniel@0: Netlab Reference Manual mdngrad Daniel@0: Daniel@0: Daniel@0: Daniel@0:

mdngrad Daniel@0:

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Daniel@0: Purpose Daniel@0:

Daniel@0: Evaluate gradient of error function for Mixture Density Network. Daniel@0: Daniel@0:

Daniel@0: Synopsis Daniel@0:

Daniel@0: 
Daniel@0: 
Daniel@0: g = mdngrad(net, x, t)
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Daniel@0: Description Daniel@0:

Daniel@0: Daniel@0: g = mdngrad(net, x, t) takes a mixture density network data Daniel@0: structure net, a matrix x of input vectors and a matrix Daniel@0: t of target vectors, and evaluates the gradient g of the Daniel@0: error function with respect to the network weights. The error function Daniel@0: is negative log likelihood of the target data. Each row of x Daniel@0: corresponds to one input vector and each row of t corresponds to Daniel@0: one target vector. Daniel@0: Daniel@0:

Daniel@0: See Also Daniel@0:

Daniel@0: mdn, mdnfwd, mdnerr, mdnprob, mlpbkp
Daniel@0: Pages: Daniel@0: Index Daniel@0:
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Copyright (c) Ian T Nabney (1996-9) Daniel@0:

David J Evans (1998) Daniel@0: Daniel@0: Daniel@0: