Building Recurrent Neural Networks to Implement Multiple Attractor Dynamics Using the Gradient Descent Method

Figure 3

Error and Kullback-Leibler divergence between the teaching sequences and output generated by the RNN for 20 000 learning steps in experiment 1.

(a)

(b)