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Phase-only signal reconstruction
ICASSP '80. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005In this paper, we develop a set of conditions under which a sequence is uniquely specified by the phase or samples of the phase of its Fourier transform. These conditions are applicable to mixed-phase one-dimensional and multi-dimensional sequences. Under the specified conditions, we also present several algorithms which may be used to reconstruct a ...
Monson H. Hayes +2 more
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Using ADZT for a signal reconstruction
2013 European Conference on Circuit Theory and Design (ECCTD), 2013The Approximate Discrete Zolotarev Transform (ADZT) has been introduced recently. The aim of this paper is to describe the possibilities and limitations of ADZT when used for a signal reconstruction. The signal reconstruction is shown for three types of signals. Only one signal segment is used, that is why there is no need of an overlap-add (or overlap-
Pavel Masa +3 more
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An Effective LFM Signal Reconstruction Method for Signal Denoising
Journal of Circuits, Systems and Computers, 2018One of the main challenges in signal denoising is to accurately restore useful signals in low signal-to-noise ratio (SNR) scenarios. In this paper, we investigate the signal denoising problem for multi-component linear frequency modulated (LFM) signals. An effective time-frequency (TF) analysis-based approach is proposed.
Luo, Shan +4 more
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Bispectral reconstruction of signals in noise: amplitude reconstruction issues
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990Two solutions to the problem of recovering deterministic signals (objects) from the bispectrum of noisy observations of the signal are proposed. Some of the tradeoffs involved in using bispectrum-based reconstruction approaches vis-a-vis other techniques are discussed. Applications to several types of problems are discussed.
Gopal Sundaramoorthy +2 more
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Large-Scale Signaling Network Reconstruction
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2012Reconstructing the topology of a signaling network by means of RNA interference (RNAi) technology is an underdetermined problem especially when a single gene in the network is knocked down or observed. In addition, the exponential search space limits the existing methods to small signaling networks of size 10-15 genes.
Seyedsasan Hashemikhabir +4 more
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A recursive approach to reconstruction of sparse signals
2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014Compressive Sensing (CS) theory details how a sparsely represented signal in a known basis can be reconstructed using less number of measurements. In many practical systems, the observation signal has a sparse representation in a continuous parameter space. This situation rises the possibility of use of the CS reconstruction techniques in the practical
Oguzhan Teke +2 more
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Adaptive signal reconstruction
Fourth Symposium on Adaptive Processes, 1965An adaptive filter which reconstructs a continuous signal from its samples is described. This filter is based on the minimum mean-square-error reconstruction filter, assuming an all-pole model for the sampled spectral density of the input signal. The use of this model leads to two important simplifications.
S. Tretter, K. Steiglitz
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Iterative signal reconstruction of deliberately clipped SMT signals
Science China Information Sciences, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zsolt Kollár +4 more
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Time-frequency signal reconstruction of nonsparse audio signals
2017 22nd International Conference on Digital Signal Processing (DSP), 2017In this paper, the reconstruction of non-stationary audio signals is considered. Audio signals are approximately sparse in the joint time-frequency representation domain. The reconstruction is based on a reduced set of samples, and it is considered that the signals are sparse.
Isidora Stankovic +2 more
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Reconstructing the Hippo signaling network
Science Bulletin, 2023Zhenxing, Zhong +2 more
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