Matrix analysis
Iterative reconstruction of multivariate band-limited functions from irregular sampling values
SIAM Journal on Mathematical Analysis
Efficient numerical methods in non-uniform sampling theory
Numerische Mathematik
Fast Iterative Reconstruction of Band-Limited Images from Non-Uniform Sampling Values
CAIP '93 Proceedings of the 5th International Conference on Computer Analysis of Images and Patterns
Locating and correcting errors in images
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Recovery of signals from nonuniform samples using iterative methods
IEEE Transactions on Signal Processing
Efficient algorithms for burst error recovery using FFT and othertransform kernels
IEEE Transactions on Signal Processing
The eigenvalues of matrices that occur in certain interpolationproblems
IEEE Transactions on Signal Processing
Noniterative and fast iterative methods for interpolation andextrapolation
IEEE Transactions on Signal Processing
Subspace-based error and erasure correction with DFT codes for wireless channels
IEEE Transactions on Signal Processing
Interpolation and the discrete Papoulis-Gerchberg algorithm
IEEE Transactions on Signal Processing
Performance analysis and recursive syndrome decoding of DFT codes for bursty erasure recovery
IEEE Transactions on Signal Processing
Frame-theoretic analysis of DFT codes with erasures
IEEE Transactions on Signal Processing
Coding of Real-Number Sequences for Error Correction: A Digital Signal Processing Problem
IEEE Journal on Selected Areas in Communications
Computationally attractive reconstruction of bandlimited images from irregular samples
IEEE Transactions on Image Processing
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This paper proposes a new approach for improving the stability of discrete Fourier transform (DFT) codes for burst error recovery. The decoding algorithms for DFT codes become unstable in burst error situations because of the ill-conditioned matrices that arise in the recovery algorithms. This paper proposes a collection of oversampling patterns instead of consecutive zero oversampling and proves the ability to recover the original signal. Also the effects of these oversampling patterns on the stability of recovery algorithms are studied. This paper proves that these patterns greatly improve the stability of these algorithms in burst error situations. The effect of some special kinds of sparse error patterns on the proposed method is analyzed and a method is suggested to avoid this situation. The simulation results include different situations and error patterns and their effect on DFT codes. These experimental results also show the robustness of the proposed method against the quantization noise and burst of errors.