Uncertainty principle plays an important role in physics, mathematics, signal processing and et al. In this paper, based on the definition and properties of discrete linear canonical transform (DLCT), we introduced th...Uncertainty principle plays an important role in physics, mathematics, signal processing and et al. In this paper, based on the definition and properties of discrete linear canonical transform (DLCT), we introduced the discrete HausdorffYoung inequality. Furthermore, the generalized discrete Shannon entropic uncertainty relation and discrete Rényi entropic uncertainty relation were explored. In addition, the condition of equality via Lagrange optimization was developed, which shows that if the two conjugate variables have constant amplitudes that are the inverse of the square root of numbers of non-zero elements, then the uncertainty relations touch their lowest bounds. On one hand, these new uncertainty relations enrich the ensemble of uncertainty principles, and on the other hand, these derived bounds yield new understanding of discrete signals in new transform domain.展开更多
Linear canonical transformation(LCT)is a generalization of the Fourier transform and fractional Fourier transform.The recent research has shown that the LCT is widely used in signal processing and applied mathematics,...Linear canonical transformation(LCT)is a generalization of the Fourier transform and fractional Fourier transform.The recent research has shown that the LCT is widely used in signal processing and applied mathematics,and the discretization of the LCT becomes vital for the applic-ations of LCT.Based on the development of discretization LCT,a review of important research progress and current situation is presented,which can help researchers to further understand the discretization of LCT and can promote its engineering application.Meanwhile,the connection among different discretization algorithms and the future research are given.展开更多
文摘Uncertainty principle plays an important role in physics, mathematics, signal processing and et al. In this paper, based on the definition and properties of discrete linear canonical transform (DLCT), we introduced the discrete HausdorffYoung inequality. Furthermore, the generalized discrete Shannon entropic uncertainty relation and discrete Rényi entropic uncertainty relation were explored. In addition, the condition of equality via Lagrange optimization was developed, which shows that if the two conjugate variables have constant amplitudes that are the inverse of the square root of numbers of non-zero elements, then the uncertainty relations touch their lowest bounds. On one hand, these new uncertainty relations enrich the ensemble of uncertainty principles, and on the other hand, these derived bounds yield new understanding of discrete signals in new transform domain.
基金supported by the National Natural Science Found-ation of China(No.62001193).
文摘Linear canonical transformation(LCT)is a generalization of the Fourier transform and fractional Fourier transform.The recent research has shown that the LCT is widely used in signal processing and applied mathematics,and the discretization of the LCT becomes vital for the applic-ations of LCT.Based on the development of discretization LCT,a review of important research progress and current situation is presented,which can help researchers to further understand the discretization of LCT and can promote its engineering application.Meanwhile,the connection among different discretization algorithms and the future research are given.
