Daniel@0: Daniel@0: Daniel@0: Daniel@0: Netlab Reference Manual demolgd1 Daniel@0: Daniel@0: Daniel@0: Daniel@0:

demolgd1 Daniel@0:

Daniel@0:

Daniel@0: Purpose Daniel@0:

Daniel@0: Demonstrate simple MLP optimisation with on-line gradient descent Daniel@0: Daniel@0:

Daniel@0: Synopsis Daniel@0:

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Daniel@0: demolgd1
Daniel@0: Daniel@0: Daniel@0:

Daniel@0: Description Daniel@0:

Daniel@0: The problem consists of one input variable x and one target variable Daniel@0: t with data generated by sampling x at equal intervals and then Daniel@0: generating target data by computing sin(2*pi*x) and adding Gaussian Daniel@0: noise. A 2-layer network with linear outputs is trained by minimizing a Daniel@0: sum-of-squares error function using on-line gradient descent. Daniel@0: Daniel@0:

Daniel@0: See Also Daniel@0:

Daniel@0: demmlp1, olgd
Daniel@0: Pages: Daniel@0: Index Daniel@0:
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Copyright (c) Ian T Nabney (1996-9) Daniel@0: Daniel@0: Daniel@0: Daniel@0: