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<html><head><title>Netlab Reference Manual mdn</title></head><body><H1> mdn</H1><h2>Purpose</h2>Creates a Mixture Density Network with specified architecture.<p><h2>Synopsis</h2><PRE>net = mdn(nin, nhidden, ncentres, dimtarget)net = mdn(nin, nhidden, ncentres, dimtarget, mixtype, ... prior, beta)</PRE><p><h2>Description</h2><CODE>net = mdn(nin, nhidden, ncentres, dimtarget)</CODE> takes the number of inputs, hidden units for a 2-layer feed-forward network and the number of centres and target dimension for the mixture model whose parameters are set from the outputs of the neural network.The fifth argument <CODE>mixtype</CODE> is used to define the type of mixturemodel. (Currently there is only one type supported: a mixture of Gaussians witha single covariance parameter for each component.) For this model,the mixture coefficients are computed from a group of softmax outputs,the centres are equal to a group of linear outputs, and the variances are obtained by applying the exponential function to a third group of outputs.<p>The network is initialised by a call to <CODE>mlp</CODE>, and the arguments<CODE>prior</CODE>, and <CODE>beta</CODE> have the same role as for that function.Weight initialisation uses the Matlab function <CODE>randn</CODE> and so the seed for the random weight initialization can be set using <CODE>randn('state', s)</CODE> where <CODE>s</CODE> is the seed value.A specialised data structure (rather than <CODE>gmm</CODE>)is used for the mixture model outputs to improvethe efficiency of error and gradient calculations in network training.The fields are described in <CODE>mdnfwd</CODE> where they are set up.<p>The fields in <CODE>net</CODE> are<PRE> type = 'mdn' nin = number of input variables nout = dimension of target space (not number of network outputs) nwts = total number of weights and biases mdnmixes = data structure for mixture model output mlp = data structure for MLP network</PRE><p><h2>Example</h2><PRE>net = mdn(2, 4, 3, 1, 'spherical');</PRE>This creates a Mixture Density Network with 2 inputs and 4 hidden units.The mixture model has 3 components and the target space has dimension 1.<p><h2>See Also</h2><CODE><a href="mdnfwd.htm">mdnfwd</a></CODE>, <CODE><a href="mdnerr.htm">mdnerr</a></CODE>, <CODE><a href="mdn2gmm.htm">mdn2gmm</a></CODE>, <CODE><a href="mdngrad.htm">mdngrad</a></CODE>, <CODE><a href="mdnpak.htm">mdnpak</a></CODE>, <CODE><a href="mdnunpak.htm">mdnunpak</a></CODE>, <CODE><a href="mlp.htm">mlp</a></CODE><hr><b>Pages:</b><a href="index.htm">Index</a><hr><p>Copyright (c) Ian T Nabney (1996-9)<p>David J Evans (1998)</body></html>⌨️ 快捷键说明
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