I have a dataset of shape
105 x 501 x 266 where
105 is the number of data and
501 x 266 is the shape of
1 data i.e. The labels_dataset is of shape
105 x 1.
Each value of the
501 x 266 matrix is a complex number.
So it essentially becomes
501 * 266 * 2(real and imaginary part of the number)
And now I have to feed this data to a CNN. I 'm new to training networks. So need to know whether my data is in best possible form for the CNN or not.
I've printed out max, min, sd, mean of real part, imaginary part and magnitude of the dataset for more info:
max real = 0.186396, min real = -0.204375 max imag = 0.166608, min imag = -0.159017 max abs = 0.219019, min abs = 2.33527e-10 mean real = 4.01718e-10, complex = 6.79294e-15, abs = 8.82916e-05 std dev real = 0.000442753, complex = 0.000400677, abs = 0.000590573
Is this a good form of data for input to a CNN. What are the options to make it more suitable?