I need help on configuring a neural network. I would like to pass in accelerometer values (x,y,z) from two different sensors, and have the network compute the corresponding angle. I am providing close to 80,000 training data points for which I provide the accelerometer values and the corresponding angles. When I developed a neural network with only 1 sensor, the network performed and computed the desired angles quite well. However, the issue I am having with using two sensors is that the x,y,z values of the first sensor are all related (or belong to one class), and the x,y,z values of the second sensor are all related. How can I tell the neural network to consider the first set or combination of x,y,z accelerometer values together, and then the second set of x,y,z accelerometer values together, then somehow use these two sets of data together to evaluate the angle. Just a note, the accelerometer values essentially indicate the orientation of the sensor. So I need to consider the orientation of the two sensors in order to find my desired angle.
Any suggestions are much appreciated. I am using the neural network toolbox in Matlab, but am open to using other methods for analysis.