Figure 1
From: Should Hebbian learning be selective for negative excess kurtosis?
The learning rule's ability to perform an independent component analysis is tested with the non-linear bars problem. An input set consisting of a random number of horizontal and vertical bars is fed to the neuron which, after training, becomes selective to individual bars or pixels, the independent components of the input set, even when such an input was never presented to the neuron in isolation.