Figure 9. The performance of the chronotron learning rules for a classification problem.

The input patterns are classified into 3 classes. (A)–(C) The average minimum number of epochs required for correct learning is displayed as a function of the load , for various values of the number of input synapses . Note the scale differences. (A) E-learning. (B) I-learning. (C) ReSuMe. (D) The maximum load for which correct learning can be achieved (the capacity ), as a function of . E-learning has a much better performance than I-learning or ReSuMe. For E-learning, simulations for higher were not performed because of the high computational cost, due to the high capacity resulted through this learning rule. Averages were computed over 500 realizations with different, random initial conditions.