📄 rbfderiv.htm
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<html><head><title>Netlab Reference Manual rbfderiv</title></head><body><H1> rbfderiv</H1><h2>Purpose</h2>Evaluate derivatives of RBF network outputs with respect to weights.<p><h2>Synopsis</h2><PRE>g = rbfderiv(net, x)</PRE><p><h2>Description</h2><CODE>g = rbfderiv(net, x)</CODE> takes a network data structure <CODE>net</CODE>and a matrix of input vectors <CODE>x</CODE> and returns a three-index matrix<CODE>g</CODE> whose <CODE>i</CODE>, <CODE>j</CODE>, <CODE>k</CODE> element contains thederivative of network output <CODE>k</CODE> with respect to weight or biasparameter <CODE>j</CODE> for input pattern <CODE>i</CODE>. The ordering of theweight and bias parameters is defined by <CODE>rbfunpak</CODE>. Thisfunction also takes into account any mask in the network data structure.<p><h2>See Also</h2><CODE><a href="rbf.htm">rbf</a></CODE>, <CODE><a href="rbfpak.htm">rbfpak</a></CODE>, <CODE><a href="rbfgrad.htm">rbfgrad</a></CODE>, <CODE><a href="rbfbkp.htm">rbfbkp</a></CODE><hr><b>Pages:</b><a href="index.htm">Index</a><hr><p>Copyright (c) Ian T Nabney (1996-9)</body></html>⌨️ 快捷键说明
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