Training a perceptron by a bit sequence: Storage capacity
  A perceptron is trained by a random bit sequence. In comparison to the corresponding classification problem, the storage capacity decreases to alpha_c=1.70\pm 0.02 due to correlations between input and output bits. The numerical results are supported by a signal to noise analysis of Hebbian weights. 
M. Schroeder, W. Kinzel and I. Kanter