@@ -20,7 +20,7 @@ Run the following commands inside the CSNN folder:
Remember to build again if you change the source code.
### How to use CSNN
Once the `make` command is finished, you should see binary files which represent each simulation.
Once the `make` command is done, you should see binary files representing each simulation.
Run a simulation:
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@@ -34,7 +34,7 @@ For example: to run MNIST simulation without compression and reinforcement:
./Mnist 0 0
In the `apps` folder, you find the source code for each simulation where you can change the architecture, the network parameters, or activate the [layerwise compression](https://gitlab.univ-lille.fr/hammouda.elbez/progressive-layer-based-compression-for-convolutional-spiking-neural-network/-/blob/main/CSNN-Simulator/apps/Mnist.cpp#L21).
In the `apps` folder, you will find the source code for each simulation, where you can change the architecture and the network parameters or activate the [layerwise compression](https://gitlab.univ-lille.fr/hammouda.elbez/progressive-layer-based-compression-for-convolutional-spiking-neural-network/-/blob/main/CSNN-Simulator/apps/Mnist.cpp#L21).
## Going from CSNN to SpiNNaker
To transfer the learned weights from CSNN to SpiNNaker, we use the following command:
