Neural Network Toolbox™

Change network weights and biases to previous initialization values

Syntax

• net = revert(net)
  

Description

revert (net) returns neural network net with weight and bias values restored to the values generated the last time the network was initialized.

If the network is altered so that it has different weight and bias connections or different input or layer sizes, then revert cannot set the weights and biases to their previous values and they are set to zeros instead.

Examples

Here a perceptron is created with a two-element input (with ranges of 0 to 1 and -2 to 2) and one neuron. Once it is created, you can display the neuron's weights and bias.

• net = newp([0 1;-2 2],1);
  

The initial network has weights and biases with zero values.

• net.iw{1,1}, net.b{1}
  

Change these values as follows:

• net.iw{1,1} = [1 2]; 
  net.b{1} = 5;
  net.iw{1,1}, net.b{1}
  

You can recover the network's initial values as follows:

• net = revert(net);
  net.iw{1,1}, net.b{1}
  

See Also

init, sim, adapt, train

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