SOLVERB Design radial basis network.
This function is obselete.
Use NEWRB to design your network.
NEWRB Design a radial basis network.
Synopsis
net = newrb
[net,tr] = newrb(P,T,GOAL,SPREAD,MN,DF)
Description
Radial basis networks can be used to approximate
functions. NEWRB adds neurons to the hidden
layer of a radial basis network until it meets
the specified mean squared error goal.
NET = NEWRB creates a new network with a dialog box.
NEWRB(PR,T,GOAL,SPREAD,MN,DF) takes these arguments,
P - RxQ matrix of Q input vectors.
T - SxQ matrix of Q target class vectors.
GOAL - Mean squared error goal, default = 0.0.
SPREAD - Spread of radial basis functions, default = 1.0.
MN - Maximum number of neurons, default is Q.
DF - Number of neurons to add between displays, default = 25.
and returns a new radial basis network.
The larger that SPREAD is the smoother the function approximation
will be. Too large a spread means a lot of neurons will be
required to fit a fast changing function. Too small a spread
means many neurons will be required to fit a smooth function,
and the network may not generalize well. Call NEWRB with
different spreads to find the best value for a given problem.
[ 本帖最后由 花如月 于 2007-11-27 11:21 编辑 ] |