Efficient numerical methods in non-uniform sampling theory
Numerische Mathematik
Irregular sampling, Toeplitz matrices, and the approximation of entire functions of exponential type
Mathematics of Computation
Sampling of linear canonical transformed signals
Signal Processing
New sampling formulae related to linear canonical transform
Signal Processing
Recovery of signals from nonuniform samples using iterative methods
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Approximating Signals From Nonuniform Continuous Time Samples at Unknown Locations
IEEE Transactions on Signal Processing
On Sampling of Band-Limited Signals Associated With the Linear Canonical Transform
IEEE Transactions on Signal Processing
Eigenfunctions of linear canonical transform
IEEE Transactions on Signal Processing
The fractional Fourier transform and time-frequency representations
IEEE Transactions on Signal Processing
Speech recovery based on the linear canonical transform
Speech Communication
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The sampling theory describes ways of reconstructing signals from their uniform or nonuniform samples associated with the traditional Fourier transform (FT). Most of the published papers about the sampling theory require signals to be bandlimited in the FT domain and assume that the sample locations and the band width are all known. However, the sample locations are not always known and most of the signals are non-stationary in practical applications. In order to overcome these shortcomings, this paper provides an algorithm for approximating signals from nonuniform samples at unknown locations. These signals are not necessarily bandlimited in the FT domain, however bandlimited in the LCT domain. The experimental results are given to verify the accuracy of the algorithm.