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Sampling of signals and their reconstruction
International Journal of Systems Science, 1976This paper gives error bounds when a stochastic process or a deterministic signal is sampled and reconstruction is done either by piecewise straight lines or cubic splines. In the case of cubic splines the error bounds derived here take into account the number of samples.
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[1991] Proceedings of the 34th Midwest Symposium on Circuits and Systems, 2002
It is pointed out that modular signal reconstruction (MSR) allows for very simple and compact VLSI implementations. The idea is to process the derivative (or successive difference) of the signal using modular arithmetic and reconstruct the answer by integrating.
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It is pointed out that modular signal reconstruction (MSR) allows for very simple and compact VLSI implementations. The idea is to process the derivative (or successive difference) of the signal using modular arithmetic and reconstruct the answer by integrating.
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Reconstruction of Real Signals
2008 International Conference on Computer and Electrical Engineering, 2008We consider a real signal which has been sampled synchronously and uniformly at two sampling frequencies, the first equal to its bandwidth, and the second to 150% of its bandwidth. Therefore the two corresponding discrete-time signals are undersampled versions of the original analog signal.
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Consistent Sampling and Efficient Signal Reconstruction
IEEE Signal Processing Letters, 2009We propose efficient signal reconstruction methods such that the reconstructed signal has the same measurements as the underlying original signal if the former was observed by the same system as that for the latter. The reconstructed signal is a linear combination of reconstruction functions, and the main task is to compute the coefficients from the ...
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Sampling and Reconstruction of Signals
2017The method of obtaining the discrete sequence from the continuous signal by sampling the continuous signal with the sampling frequency Fs is described in this chapter. This chapter covers Fourier series, Fourier transformation, Discrete Time Fourier Transformation, Discrete Fourier Transformation, Laplace transformation and the Z-transformation.
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Sparse signal reconstruction via collaborative neurodynamic optimization
Neural Networks, 2022Jun Wang +2 more
exaly
The signal reconstruction of speech by KPCA
6th International Conference on Spoken Language Processing (ICSLP 2000), 2000Hui Yan +4 more
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Signal Reconstruction and Coding
2001Consider a low-pass signal with N samples where the amplitude of t samples was modified. Is it possible to find a method to detect which samples violate the low-pass condition and reconstruct their original amplitude? Most of the known techniques of signal reconstruction don’t solve this problem, being necessary to know the error positions in order to ...
Vieira, José Manuel Neto +1 more
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A sparsity adaptive compressed signal reconstruction based on sensing dictionary
Journal of Systems Engineering and Electronics, 2021Shen Zhiyuan
exaly