Nonlinear Blind Equalization for Volume Holographic Data Storage
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Abstract
We investigate the nonlinear blind equalization for volume holographic data storage channel. Base on the recurrent neural network channel model, we describe a novel blind equalizer for the volume holographic data storage system to improve the bit error rate and hence to make the storage densities achievable. The experimental results also indicate that a significant improvement in the bit error rate to 2.55×103 is possible with the nonlinear blind equalization.
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