Abstract
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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