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# lyngby_nn_cddevds

## (export/lyngby/lyngby_nn_cddevds.m)

### Function Synopsis

ddEV = lyngby_nn_cddevds(X, Y, V, W, H12)

### Help text

lyngby_nn_cddevds - 2nd order, entropic, input, diag. sym.
function ddEV = lyngby_nn_cddevds(X, Y, V, W, H12)
Input: X Neural network input
Y Neural network output
W Output weights
H12 One minus Hidden layer in 2nd power
Output: ddEV Derivative, a vector
'Symmetric' diagonal approximation to the second order
derivative of the entropic error function with respect
to the input weights.
H12 can be computed as (1-H.^2)
See also: lyngby_nn_cddewds, lyngby_nn_cdev

### Cross-Reference Information

This function is called by

Produced by mat2html on Wed Jul 29 15:43:40 2009

Cross-Directory links are: OFF