This paper proposes a new model of a neural network-pseudo-optical neural networks (PONNs), consisting of interfering neurons whose potential varies as a result of the interference of the input periodic signals. The phase differences of the signals depend on the bond lengths between the neurons, and therefore the geometry of the network is essential. A class of PONNs is studied that is called the complete rectilinear model. The holographic and other optical effects in such networks are analyzed.

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