MATLAB: NARXNET with input delay

Question

Hi,

I am solving a problem incorporating measurement delay in a sensor. I have a set of measured acceleration based on the sensor reading (in time series). However, the measurements that I obtained have some time delay from the 'true' value of it. I want to design a neural network that can 'predict' the true acceleration value using the measured value that I obtained from the sensor measurement.

I am using NARXNET to model the neural network of it. To accommodate the delay in the input, 'inputDelays' is adjusted according to the delay in the sensor measurement (and, technically, no delay is needed for the 'feedbackDelays'). Am I doing it correctly?

Thank you,

Ghazi

Answer 1

No.

TIMEDELAYNET is used to predict an output series, y, using an exogeneous external input series x.

NARXNET is used to predict an output series, y, using BOTH an exogeneous external input series x, along with feedback signals from the previous estimated values of y.

HOWEVER, you do not have an exogeneous external input series!

Therefore, you should use NARNET. First read the documentation

 help narnet
 doc narnet

Then search for some of my posts in BOTH the NEWSGROUP AND ANSWERS using

 narnet greg

and

 narnet greg tutorial

Begin by finding the statistically significant nonzero lags at the highest local peaks of the measurement autocorrelation function. Search

 nncorr narnet

Then use as small a continuous subset of lags as needed for your predictions.

Hope this helps.

Thank you for formally accepting my answer

Greg