Gradient Calculations for Dynamic Recurrent Neural Networks

This chapter contains sections titled:

• Introduction

• Learning in Networks with Fixed Points

• Computing the Gradient Without Assuming a Fixed Point

• Some Simulations

• Stability and Perturbation Experiments

• Other Non-Fixed-Point Techniques

• Learning with Scale Parameters

• Conclusion

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