Closedloop Recurrent Neural Network problem
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My closed loop network response is random numbers between +ve and -ve values while the open loop network performance reaches to 1e-12.
I have a model with 9 outputs and 7 inputs. I generate the outputs using series of sine functions with different frequencies. I measure the input from the inverse model (which I have), and the model has first/second order differentiations.
Is the problem in my data? cause I read many answers here about problems in closedloop responses differ than the openloop?
I appreciate any help.
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Greg Heath
2013-3-27
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I have 3 suggestions.
1. Only use significant delays obtained from the target autocorrelation function and target/input cross-correlation function.
2. Minimize H given ID, FD, and MSE <= 0.005*mean(var(target',1))
3. Do not use the default dividerand. Instead, use divideblock or divideind.
Hope this helps.
Greg
更多回答（2 个）
Greg Heath
2013-3-27
0 个投票
I know this is not a good answer, but I and others are also having closeloop performance problems. So far I haven't found out why.
Greg
Greg Heath
2013-3-28
Assume a 1-dimensional training target of length N
1. xcorrtn = nncorr(zscore(ttrn,1),zscore(randn(1,N)),N-1,'biased');
2. Sort the absolute values
3. Find the value 95% of the way to the end.
4. Repeat 100 times and take the average
Use that value as the 95% confidence threshold value for the significant auto and cross correlations of ttrn.
Greg
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