The extrapolation of bandlimited signals in the offset linear canonical transform domain

Xu, Shuiqing; Tao, Songbing; Chai, Yi; Yang, Xi; He, Yigang

doi:10.1016/j.ijleo.2018.11.126

Cited by 10 publications

(5 citation statements)

References 34 publications

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“…The extrapolation of band-limited signals is widely applied in Engineering, Seismology, Industrial Electronics and other fields [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

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Fast algorithms for band-limited extrapolation by over sampling and Fourier series

Chen

2023

EURASIP J. Adv. Signal Process.

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In this paper, fast algorithms for the extrapolation of band-limited signals are presented by the sampling theorem and Fourier series in the case of over sampling. Assume the band-limited signal is known in a finite interval. We update the signal outside the interval by the Shannon sampling theorem in the case of over sampling. Then we obtain a fast algorithm in the form of Fourier series instead of the Fourier transform in the Papoulis–Gerchberg algorithm. Gibbs phenomena is analyzed in the method. An algorithm is presented to control the Gibbs phenomena, and some examples are given in the experimental results.

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Section: Introductionmentioning

confidence: 99%

“…In [4], the application of the extrapolation in spectral estimation is described. In [5][6][7][8][9][10][11][12][13][14], other extrapolation algorithms are presented. In [15,16], applications of extrapolation and regularization method in image restoration are given.…”

Section: Introductionmentioning

confidence: 99%

Fast algorithms for band-limited extrapolation by over sampling and Fourier series

Chen

2023

EURASIP J. Adv. Signal Process.

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“…The reconstruction of a stream of pulses for ultrasonic imaging was proposed using a noiseless finite rate innovation (FRI) method [16,17]. Many low-pass reconstruction problems have been successfully resolved via extrapolation [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Noise Effects on a Proposed Algorithm for Signal Reconstruction and Bandwidth Optimization

Ashour

Khalaf

Hussein

et al. 2023

Int. j. electr. comput. eng. syst. (Online)

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The development of wireless technology in recent years has increased the demand for channel resources within a limited spectrum. The system's performance can be improved through bandwidth optimization, as the spectrum is a scarce resource. To reconstruct the signal, given incomplete knowledge about the original signal, signal reconstruction algorithms are needed. In this paper, we propose a new scheme for reducing the effect of adding additive white Gaussian noise (AWGN) using a noise reject filter (NRF) on a previously discussed algorithm for baseband signal transmission and reconstruction that can reconstruct most of the signal’s energy without any need to send most of the signal’s concentrated power like the conventional methods, thus achieving bandwidth optimization. The proposed scheme for noise reduction was tested for a pulse signal and stream of pulses with different rates (2, 4, 6, and 8 Mbps) and showed good reconstruction performance in terms of the normalized mean squared error (NMSE) and achieved an average enhancement of around 48%. The proposed schemes for signal reconstruction and noise reduction can be applied to different applications, such as ultra-wideband (UWB) communications, radio frequency identification (RFID) systems, mobile communication networks, and radar systems.

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“…To enlarge the application scope, algorithms based on GP algorithm are extended to signals bandlimited into more domains such as the fractional Fourier domain, wavelet domain, or linear canonical transform domain [18][19][20]. Moreover, mathematic means-like regularization methods are further adopted to lower the extrapolation error led by white noise [21,22]. The acceleration of the extrapolation method is another research direction.…”

Section: Introductionmentioning

confidence: 99%

Piecewise Iterative Extrapolation Method for Bandlimited Signal

et al. 2022

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In some high spectrally efficient communication structures, the Gerchberg-Papoulis extrapolation algorithm can be used to reconstruct nonorthogonal signals. However, the extrapolation efficiency and accuracy degrades when the energy of known signal is small or the iterative filter bandwidth is large. Focused on these drawbacks, a piecewise iterative extrapolation method is proposed to extrapolate bandlimited signals with higher extrapolation efficiency and accuracy. In this paper, the amplitude change of the unknown part over iterations is analyzed and the feasibility of the proposed extrapolation method is discussed. Numerical simulation shows the accuracy superiority of proposed method with the frequency offset compared to the GP algorithm with fixed computational complexity. Besides, the feasibility of the proposed method is verified in fractional Fourier domain with performance advantages.

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The extrapolation of bandlimited signals in the offset linear canonical transform domain

Cited by 10 publications

References 34 publications

Fast algorithms for band-limited extrapolation by over sampling and Fourier series

Fast algorithms for band-limited extrapolation by over sampling and Fourier series

Noise Effects on a Proposed Algorithm for Signal Reconstruction and Bandwidth Optimization

Piecewise Iterative Extrapolation Method for Bandlimited Signal

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