Discrete Inequalities on LCT

Q3 Computer Science
Guanlei Xu, Xiaotong Wang, Xiaogang Xu
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引用次数: 2

Abstract

Linear canonical transform (LCT) is widely used in physical optics, mathematics and information processing. This paper investigates the generalized uncertainty principles, which plays an important role in physics, of LCT for concentrated data in limited supports. The discrete generalized uncertainty relation, whose bounds are related to LCT parameters and data lengths, is derived in theory. The uncertainty principle discloses that the data in LCT domains may have much higher concentration than that in traditional domains.
LCT上的离散不等式
线性正则变换(LCT)广泛应用于物理光学、数学和信息处理等领域。本文研究了有限支撑条件下集中数据LCT的广义不确定性原理,该原理在物理学中起着重要作用。从理论上导出了离散广义不确定性关系,其界与LCT参数和数据长度有关。不确定性原理揭示了LCT域中的数据可能比传统域中的数据具有更高的集中度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.20
自引率
0.00%
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0
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