Visible light wave band optical neural network element
A neural network and visible light technology, applied in the field of image recognition and optical components, can solve the problems of inability to work in the visible light band and low diffraction efficiency of diffractive components
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specific Embodiment 1
[0050] This embodiment is an embodiment of an optical neural network element in the visible light band.
[0051] A visible light band optical neural network element of this embodiment, the structural diagram is as follows figure 1 shown. The optical neural network element in the visible light band is segmented through a single projection exposure, atomic layer deposition, etching process, and slice, and includes a plurality of subelements 1 arranged at equal intervals along the optical axis, and the subelements 1 are perpendicular to the The projection figure of the plane of the optical axis is a square, and the projection figures of all subcomponents 1 to the plane perpendicular to the optical axis coincide; each subcomponent 1 includes a substrate 2 and a plurality of substructures 3 supported by the substrate 2, such as figure 2 As shown, the substructures 3 are arranged in a matrix on the surface of the substrate 2. In the row direction and the column direction of the ma...
specific Embodiment 2
[0055] This embodiment is an embodiment of an optical neural network element in the visible light band.
[0056] An optical neural network element in the visible light band of this embodiment is further defined on the basis of the specific embodiment 1:
[0057] Define the incident light wavelength as λ d , the size (L, W, H) of each substructure 3 and the distance P between the coordinates of two adjacent substructures 3 on the substrate 2 form the parameter vector (L, W, H, P);
[0058] Wherein, L is the length of the substructure 3, W is the width of the substructure 3, and H is the height of the substructure 3;
[0059] The method for calculating substructure 3 parameter vectors (L, W, H, P) comprises the following steps:
[0060] Step a, assign a value to each parameter of (L, W, H, P), wherein the range of each parameter satisfies the following conditions: 0d and 100nmd , and each parameter is assigned an integer multiple of 5, and N L ×N W ×N H ×N P parameter ve...
specific Embodiment 3
[0072] This embodiment is an embodiment of an optical neural network element.
[0073] This embodiment is an embodiment of an optical neural network element in the visible light band.
[0074] An optical neural network element in the visible light band of this embodiment, on the basis of specific embodiment 1 or specific embodiment 2, further defines that the material of the substructure 3 is titanium dioxide or gallium nitride, and the material of the substrate 2 is silica.
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Abstract
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