Dynamical Sampling in Shift-Invariant Spaces Associated with multi-dimensional Special Affine Fourier Transform

Meng Ning, Li-Ping Wu, Qing-yue Zhang, Bei Liu
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Abstract

The Special Affine Fourier Transformation(SAFT), which generalizes several well-known unitary transformations, has been demonstrated as a valuable tool in signal processing and optics. In this paper, we explore the multivariate dynamical sampling problem in shift-invariant spaces associated with the multi-dimensional SAFT. Specifically, we derive a sufficient and necessary condition under which a function in a shift-invariant space can be stably recovered from its dynamical sampling measurements associated with the multi-dimensional SAFT . We also present a straightforward example to elucidate our main result.
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与多维特殊仿射傅里叶变换相关的移位不变量空间中的动态采样
特殊仿射傅里叶变换(SAFT)概括了几种众所周知的单元变换,已被证明是一种重要的信号处理和光学工具。在本文中,我们探讨了与多维 SAFT 相关的移位不变空间中的多变量动态采样问题。具体来说,我们推导了一个充分必要条件,在这个条件下,移变空间中的函数可以从与多维 SAFT 相关的动态采样测量中稳定地恢复出来。我们还给出了一个直接的例子来阐明我们的主要结果。
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