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How to use Neural Network Error as a Feedback Input

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Using neural network error as a feedback input helps reduce the overall network error and increase forecasting accuracy ( Wahheb et al. 2016).
How can I supply my Neural Network with its own error?
References:
Waheeb W, Ghazali R, Herawan T (2016) Ridge Polynomial Neural Network with Error Feedback for Time Series Forecasting. PLoS ONE 11(12): e0167248. https://doi.org/10.1371/journal.pone.0167248

Accepted Answer

Waddah Waheeb
Waddah Waheeb on 1 Jun 2019
The code to feed back network error as an input can be downloaded from the following link:
Hope this helps!
  3 Comments
Waddah Waheeb
Waddah Waheeb on 2 Jun 2019
Edited: Waddah Waheeb on 2 Jun 2019
During training, errors are used to update the weights. But in the given code, the past error is used as an input too. Based on the literature in time series forecasting, this type of modelling is used to model nonlinear moving-average processes (e.g., unpredictable events or past shocks) more directly. Please have a look at this link.

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More Answers (1)

Greg Heath
Greg Heath on 13 Feb 2018
THAT IS WHAT HAPPENS AUTOMATICALLY WHEN YOU TRAIN THE NET ! SEE THE FIGURE
net = train(net,x,t)
figure
Hope this helps.
Thank you for formally accepting my answer
Greg

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