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Neural Networks for Logic Circuits 被引量:2
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作者 Liu Yongcai (School of Computer Engineering and Science) 《Advances in Manufacturing》 SCIE CAS 1998年第2期60-63,共4页
Bushnell and the author proposed the neural networks for NOT, AND, OR, NAND, NOR, XOR and XNOR gates. Using these neural networks, the neural networks of any logic circuits can be constructd. From this, the consistent... Bushnell and the author proposed the neural networks for NOT, AND, OR, NAND, NOR, XOR and XNOR gates. Using these neural networks, the neural networks of any logic circuits can be constructd. From this, the consistent signals in the logic circuits will be transformed into the global minimal points of a quadratic pseudo Boolean function. Thus the neural network application in the field of circuit modeling and automatic test pattern generation can be widened. 展开更多
关键词 neural network Hopfield network quadratic pseudo boolean function k tree
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Inhomogeneous quantum codes (II): non-additive case
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作者 Weiyang WANG Keqin FENG 《Frontiers of Mathematics in China》 SCIE CSCD 2012年第3期573-586,共14页
The quantum codes have been generalized to inhomogeneous case and the stabilizer construction has been established to get additive inhomogeneous quantum codes in [Sei. China Math., 2010, 53: 2501-2510]. In this paper... The quantum codes have been generalized to inhomogeneous case and the stabilizer construction has been established to get additive inhomogeneous quantum codes in [Sei. China Math., 2010, 53: 2501-2510]. In this paper, we generalize the known constructions to construct non-additive inhomogeneous quantum codes and get examples of good d-ary quantum codes. 展开更多
关键词 Quantum code inhomogeneous code mixed code finite abeliangroup CHARACTER quadratic generalized boolean function
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