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FPGA implementation of a a neural network that recognize numbers from 0 to 9.

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ThierryBeaulieu/NeuralNetworkFPGA

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NeuralNetworkFPGA

Deep neural networks are becoming more and more used though the years. Neural networks often have two implementations. The first one is build and trained on GPUs. The weights and the bias found can then be used on a model synthesized on FPGAs. Those neural network doesn't require a large amount of energy and are quite efficient.

The purpose of this repository is to build different types of neural networks.

Execute

To run the project, use the following command:

sbt run 

Tests

To run the tests, use the following command:

sbt test

If you would like to only run the tests of the project, feel free to use:

sbt testOnly project.LFSRSpec

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FPGA implementation of a a neural network that recognize numbers from 0 to 9.

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