Generalized Uncertainty Inequalities on Fisher Information Associated with LCT

Guanlei Xu, Xiaogang Xu, Xiaotong Wang
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引用次数: 0

Abstract

Uncertainty principle plays an important role in multiple fields such as physics, mathematics, signal processing, etc. The linear canonical transform (LCT) has been used widely in optics and information processing and so on. In this paper, a few novel uncertainty inequalities on Fisher information associated with linear canonical transform are deduced. These newly deduced uncertainty relations not only introduce new physical interpretation in signal processing, but also build the relations between the uncertainty lower bounds and the LCT transform parameters a, b, c and d for the first time, which give us the new ideas for the analysis and potential applications. In addition, these new uncertainty inequalities have sharper and tighter bounds which are the generalized versions of the traditional counterparts. Furthermore, some numeric examples are given to demonstrate the efficiency of these newly deduced uncertainty inequalities.
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与LCT相关的Fisher信息的广义不确定性不等式
不确定性原理在物理、数学、信号处理等多个领域发挥着重要作用。线性正则变换在光学、信息处理等领域有着广泛的应用。这些新推导的不确定性关系不仅在信号处理中引入了新的物理解释,而且首次建立了不确定性下界与LCT变换参数a、b、c和d之间的关系,为分析和潜在应用提供了新的思路。此外,这些新的不确定性不等式具有更尖锐和更严格的边界,这是传统不等式的广义版本。此外,还给出了一些数值例子来证明这些新推导的不确定性不等式的有效性。
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CiteScore
1.10
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0.00%
发文量
2437
期刊最新文献
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