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Genetic algorithm-based encoding of neural networks
Genetic algorithm-based encoding of neural networks
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机译:基于遗传算法的神经网络编码
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摘要
Methods and systems are disclosed to reduce the memory requirement of neural networks by encoding the coefficients of a neural network during training stage and decoding them during the inference. The disclosed embodiment consists of a neural network coefficient decoder (NNCD), a genetic algorithm-based encoding system (GAbES), a coefficient encoding method (CEM), and a genetic algorithm-based neural network coefficient encoding/decoding (GANCED) system. The design is consistent with both hardware and firmware and it can be implemented by bitwise operation as a hardware accelerator or easily computed by a traditional processing unit. The disclosed embodiment reduces the memory storage requirement of hardware implementation of neural networks. This reduction speeds up the processing of neural networks and reduces the dynamic power consumption of the circuit.
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