This work focuses on 1- and 2-bit coding metamaterials by designing unit cell structures, also known as binary elements, that possess 0-, 90-, 180-, and 270-degree phase responses. Several parametric studies are mainl...
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This work focuses on 1- and 2-bit coding metamaterials by designing unit cell structures, also known as binary elements, that possess 0-, 90-, 180-, and 270-degree phase responses. Several parametric studies are mainly investigated, for instance, various coding sequence patterns and a few numbers of lattices likely 4, 8, and 12 in each bit. The RCS reduction analysis revealed a promising outcome where the distinct coding sequences exhibited way better reduction behaviour than others. For instance, coding sequences likely CS3, CS4, and CS5 exhibit excellent reduction behaviour when the lattices increase from 4 to 12. However, the 2-bit coding metamaterial exhibits superior reduction behaviours in RCS values, where the maximum points reached when adopting the CS5 design ranged from-75.2 to-55.6 dBm 2 .Concisely, the proposed coding metamaterial satisfied the target of this investigation to gain optimal RCS reduction by adopting both 1- and 2-bit design structures for terahertz frequency.
With the popularity of the internet and the development of network services, Steganography based on speech stream has become a research hotspot in information hiding. To improve the detection performance of steganalys...
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ISBN:
(纸本)9781450396899
With the popularity of the internet and the development of network services, Steganography based on speech stream has become a research hotspot in information hiding. To improve the detection performance of steganalysis of multiple steganography methods, in this paper, we proposed the Global-Local Representations Network (GLRN), which consists of a Global Correlation Extraction (GCE) module and a Local Correlation Enhancement (LCE) module. Firstly, considering the inter-class differences of different coding elements, the GCE module is used to capture the global correlation of different coding elements by using multi-channel modeling. Then, we realize that the process of global correlation extraction suffers from the loss of detailed information, so the LCE module is used to capture local correlations to complement the global features. The experiments show that the GLRN achieves the start-of-art detection performance.
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