Inverse design of polymorphic reconfigurable metamaterial absorbers based on a dual-input neural network
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DOI: 10.1088/1361-6463/ad3bbf
Abstract: In recent years, deep learning-based design methods for metamaterial absorbers have attracted much attention; however, the problem of structural homogeneity in inverse design constrains their further development. This paper, proposes a metamaterial absorber composed of… read more here.
Keywords: input neural; inverse design; metamaterial absorbers; dual input ... See more keywords