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srchhyb
meanings for different search algorithms. Some may not be used in this
function.
0 - normal; 1 - minimum step taken;
2 - maximum step taken; 3 - beta condition not met.
delta - New initial step size. Based on the current step size.
tol - New tolerance on search.
Parameters used for the hybrid bisection-cubic algorithm are:
alpha - Scale factor which determines sufficient reduction in perf.
beta
- Scale factor which determines sufficiently large step size.
bmax
- Largest step size.
scale_tol - Parameter which relates the tolerance tol to the initial step
size delta. Usually set to 20.
The defaults for these parameters are set in the training function which calls
it. See traincgf, traincgb, traincgp, trainbfg, trainoss.
Dimensions for these variables are:
Pd - No x Ni x TS cell array, each element P{i,j,ts} is a Dij x Q matrix.
Tl - Nl x TS cell array, each element P{i,ts} is an Vi x Q matrix.
Ai - Nl x LD cell array, each element Ai{i,k} is an Si x Q matrix.
where
Ni = net.numInputs
Nl = net.numLayers
LD = net.numLayerDelays
Ri = net.inputs{i}.size
Si = net.layers{i}.size
Vi = net.targets{i}.size
Dij = Ri * length(net.inputWeights{i,j}.delays)
Examples
Here is a problem consisting of inputs P and targets T that we would like to
solve with a network.
P = [0 1 2 3 4 5];
T = [0 0 0 1 1 1];
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