Matrix computations (3rd ed.)
The nonuniform discrete Fourier transform and its applications in signal processing
The nonuniform discrete Fourier transform and its applications in signal processing
Numerical analysis of the non-uniform sampling problem
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 vol. II: interpolation and extrapolation
Fast Reconstruction Methods for Bandlimited Functions from Periodic Nonuniform Sampling
SIAM Journal on Numerical Analysis
EURASIP Journal on Applied Signal Processing
Block-Based Methods for the Reconstruction of Finite-Length Signals From Nonuniform Samples
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Nonuniform Interpolation of Noisy Signals Using Support Vector Machines
IEEE Transactions on Signal Processing
Interpolation of Bounded Bandlimited Signals and Applications
IEEE Transactions on Signal Processing
Nonuniform Sampling of Periodic Bandlimited Signals
IEEE Transactions on Signal Processing - Part I
Filterbank reconstruction of bandlimited signals from nonuniformand generalized samples
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing - Part I
Design of barycentric interpolators for uniform and nonuniform sampling grids
IEEE Transactions on Signal Processing
On the eigenvalues of matrices for the reconstruction of missing uniform samples
IEEE Transactions on Signal Processing
Minimax design of low-complexity allpass variable fractional-delay digital filters
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Regularized sampling of multiband signals
IEEE Transactions on Signal Processing
Efficient signal reconstruction scheme for M-channel time-interleaved ADCs
Analog Integrated Circuits and Signal Processing
Hi-index | 35.69 |
A modification of the conventional Lagrange interpolator is proposed in this paper, that allows one to approximate a band-limited signal from its own nonuniform samples with high accuracy. The modification consists in applying the Lagrange method to the signal, but premultiplied by a fixed function, and then solving for the desired signal value. Its efficiency lies in the fact that the fixed function is independent of the sampling instants. It is shown in this paper that the function can be selected so that the interpolation error decreases exponentially with the number of samples, for the case in which the sampling instants have a maximum deviation from a uniform grid. This paper includes a low-complexity recursive implementation of the method. Its accuracy is validated in the numerical examples by comparison with several interpolators in the literature, and by deriving upper and lower bounds for its maximum error.