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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

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Greg Heath
Greg Heath 2016-2-14

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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

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Ghazi Binarandi
Ghazi Binarandi 2016-2-14
Thank you, Greg! You are always helpful.
Ghazi Binarandi
Ghazi Binarandi 2016-2-14
Hi Greg,
Now I think that NARNET may not be suitable for my problem. (Please correct me if I'm wrong!) Let me repeat the problem so I can explain it in a better way:
In my neural network, - my inputs are going to be 'measured accelerations' from the sensor reading (which is delayed from the 'true' value) - my targets are going to be the 'true accelerations'
So, I think I may use TIMEDELAYNET for this particular problem since I have delay in my input. Is the way of my thinking right?
Thanks,
Ghazi
Greg Heath
Greg Heath 2016-2-15
Hmmm, you are trying to predict the past !!!
I think you are correct in using timedelaynet.
Is there a constant delay between the true signal and the measurement?
Greg
Ghazi Binarandi
Ghazi Binarandi 2016-2-17
Yes, I am trying to predict the past! I have tried using timedelaynet and got a pretty nice result.
The delay can be approximated as a constant in the modeling, although it is not a constant in the real problem.
Thanks so much for the help!
Greg Heath
Greg Heath 2016-2-17
How do you obtain the true values you use for design targets?
Ghazi Binarandi
Ghazi Binarandi 2016-2-18
I have another type of sensor which has better performance in terms of delay. So, I could model the measurements from this sensor as the true/ideal values (these are going to be my target). Then, by training it with neural nets, I could use the sensors with delay on it, but still obtain a performance that is close to the better sensor.

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