Spectroscopy and Spectral Analysis, Volume. 42, Issue 5, 1393(2022)
Design of Subwavelength Narrow Band Notch Filter Based on Depth Learning
Fig. 2. Neural network structure
(a): Forward simulation network; (b): Reverse-design network
Fig. 3. (a) Forward simulation Loss function curve; (b) Inverse design Loss function curve
Fig. 4. Series neural network
Fig. 6. Red, green and blue are the spectral response curves reported by references, and black curves are
Fig. 7. RCWA numerical simulation curves with inverse design of series network
Black curve is target spectrum with a reflectivity of 100%; red-green-blue curves are RCWA simulation curves of reverse design with the reflectivity of 98.91%, 99.98% and 99.88% at the peak wavelengthes of 479.5, 551.0 and 607.0 nm, respectively
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Shuai-shuai ZHANG, Jun-hua GUO, Hua-dong LIU, Ying-li ZHANG, Xiang-guo XIAO, Hai-feng LIANG. Design of Subwavelength Narrow Band Notch Filter Based on Depth Learning[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1393
Category: Research Articles
Received: Mar. 5, 2021
Accepted: --
Published Online: Nov. 10, 2022
The Author Email: ZHANG Shuai-shuai (863711514@qq.com)