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Gradient Calculations for Dynamic Recurrent Neural Networks

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This chapter contains sections titled:
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