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Assignment 4 Use
MATLAB NEURAL NETWORKS TOOLBOX or the
Neunet (Desire) system to develop and study Learning process in Back-Propagation networks. The patterns to be
learned are the mapping from
to cos. The patterns are generated using a loop
in the program which varies
from 0 to 2
insteps of 2
/Npat. The output values are selected to be in the range [0,1] instead of [-1,1].
1. Train ax network to learn the patterns.
2. Modify the program so that a different activation function is used. For example try one of Bipolar hidden and output units (tanh
function linear output units 3. Test the ability of the network to generalize by presenting a set of Test patterns that the network was not trained with.
Questions 1. How many epochs are required to learn the patterns reasonably well (
01 0
tss)?
2. How many hidden units are required (There will be a range of hidden units that provide similar results)
3. What is the effect of changing
the activation function 4. How well is the
network able to generalize 5. Are there any other changes that could be made to reduce tss (not
the speed of learning Share with your friends: 
