A Frequency-Multiplexed Function-Approximation Coherent Neural Networks To Learn Phase Values by Use of Volume Hologram

We propose a frequency-multiplexed function-approximation coherent neural network to learn optical phase values by use of volume hologram. Experiments demonstrate that desired phase values are obtained as the output of the coherent neural network system.