MATLAB: Which neural network is suitable for the problem

Deep Learning Toolboxneural network

Hi,
I am working on building a neural network for some data that I have. Its a time series problem but the output is only dependent on the previous time step.
y(t) = f(x1(t),x2(t)….x150(t))
So, for each output I have 150 inputs. Now I have data for a number of timesteps.
The narxnet doesn't seem appropriate as it seems to consider the output to be a function of all previous timesteps. The relationship is highly non-linear.
Please suggest on what you think would be the best solution.
Thanks

Best Answer

> Its a time series problem but the output is only dependent on the previous time step.
This implies
 y(t) = f(x(t-1),y(t-1));
where
 size(x) = [  I N ] % I = 150
 size(y) = [  O N ] % O = 1
and can be implemented with
 net = narxnet( 1, 1, H);
However, your equation does not contain output feedback. This would mean
 y(t) = f(x(t-1));
which can be implemented with
 net = timedelaynet(1,H);
> The narxnet doesn't seem appropriate as it seems to consider the output to be a function of all previous timesteps.
Incorrect.
 net = narxnet(ID,FD,H);
where
ID is an increasing finite sequence of nonnegative, not necessarily consecutive or equally spaced integers
FD is an increasing finite sequence of positive, not necessarily consecutive or equally spaced, integers
> Please suggest on what you think would be the best solution
 1. Substantially reduce the input dimensionality. Using a reduced variable linear model obtained from STEPWISE or STEPWISEFIT may be adequate 
for choosing the nonlinear neural net input variables.
 2. Try the simple timedelaynet model with H no larger than necessary.
 3.If unsuccessful, try the narxnet model H no larger than necessary.
Hope this helps.
Thank you for formally accepting my answer
Greg
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