Abstract
AbstractIn the data‐driven society, fidelity and accuracy of automatic decisions behind the scene rely fundamentally on a solid data or imaging acquisition system. However, conventional microwave imagers are inadequate relating to their resolution and noise capability, mainly due to the limited aperture size and rigid working principle. Here, a programmable metasurface imager with high‐resolution and anti‐interference performance is proposed. By implementing the structure of multilayer perceptron network in the analog domain, the metasurface‐based microwave imager intelligently adapts to different datasets through illuminating a set of designed scattering patterns that mimic the feature patterns. A prototype imager system working at microwave frequency is designed and fabricated. The accuracy rate rises by 18% under the classification task of MNIST dataset, with a decline in the reconstruction imaging error. The authors experimentally demonstrate that the resolution to distinguish strip patterns goes beyond to one‐fifth of the equivalent wavelength on the target plane.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.