FRI sampling and reconstruction of asymmetric pulses

Nagesh, Sudarshan; Seelamantula, Chandra Sekhar

doi:10.1109/icassp.2015.7179115

Cited by 8 publications

(2 citation statements)

References 13 publications

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“…First, we compared the model‐matching performance of models for ideal and non‐ideal piecewise polynomials to a non‐ideal rectangular pulse sampled by oscilloscope at a rate of 2 GHz. Note that the OSR [4] is the ratio between the actual sampling rate

f_{normals} = false(false(2 N + 1 false) / T false)

and the minimum FRI sampling rate defined by

f_{normalsmin} = false(false(4 \tilde{K} + 1 false) / T false)

, i.e.

OSR \approx N / 2 \tilde{K}

. When OSR = 4,

K = 2

P = 30

and

R = 0

, the recovered signals by fitting these two models are depicted in Fig.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…Parameters can be perfectly estimated by a modified annihilating filter. Several factors are analysed to inspect the anti‐noise ability of our proposed model, such as the number of divided pieces and the oversampling ratio (OSR) [4]. Also, compared with the FRI model of ideal piecewise polynomials, our proposed model is verified to have a better matching performance for real non‐ideal signals.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Innovation rate sampling of non‐ideal piecewise polynomials

Huang

Sun

et al. 2018

Electron. lett.

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Recent sampling results show that ideal piecewise polynomials can be modelled as finite-rate-of-innovation (FRI) signals and perfectly recovered by spectral estimation. However, there is no any generic FRI model for non-ideal piecewise polynomials. An FRI model is proposed as an extension of the VPW-FRI (pulses with variable width) model for non-ideal piecewise polynomials which have uncertain transition zones near discontinuity points. The derivative of non-ideal piecewise polynomials as differentiated VPW pulse streams is assumed. The proposed model can be sampled by arbitrary kernels and recovered by a modified annihilating filter. For the extended model, simulation results analyse several factors that affect the model anti-noise property and verify its superiority of better matching performance for real non-ideal signals in comparison of the FRI model for ideal piecewise polynomials.

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