Fig. 4: Experimental demonstration of the unidirectional-bidirectional-unidirectional DNN letter classifier. | Nature Communications

Fig. 4: Experimental demonstration of the unidirectional-bidirectional-unidirectional DNN letter classifier.

From: Polarization-selective unidirectional and bidirectional diffractive neural networks for information security and sharing

Fig. 4

a, b Schematic of the working principle of the unidirectional-bidirectional-unidirectional DNN under x-, 45°-, and y-polarized THz illumination from the forward (a) and backward (b) directions. c–f Letter patterns and corresponding measured electric-field intensity distributions in the output plane under the forward incidence of x-, 45°-, and y-polarized THz waves. g–j Letter patterns and corresponding measured electric-field intensity distributions in the output plane under the backward incidence of x-, 45°-, and y-polarized THz waves. k–n Measured output-energy distribution maps for the x-polarized forward incidence. o Measured confusion matrix for the x-polarized forward incidence.

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