| # Trainable Neural Network |
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| Implements a simple neural network that supports on-chip training in addition to inference. |
| The two hidden layers use leaky ReLU as their activation function while the output layer uses a |
| rough approximation of softmax. |
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| Unlike usual neural network implementations we use fixed-point saturation arithmetic and |
| each neuron and synapse is represented as an individual instance. |
| Inputs, outputs and weights, as well as forward and backward propagation can be managed |
| through the wishbone bus. |
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