 As mentioned before, the training of an autoencoder is performed through Backpropagation of the error, just like a regular feedforward neural network.Should the feature space formula_23 have lower dimensionality than the input space formula_24, the feature vector formula_25 can be regarded as a compressed representation of the input formula_26.This is the case of "undercomplete" autoencoders.