Results 271 to 280 of about 256,514 (313)
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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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Evolutionary algorithms for sparse signal reconstruction
Signal, Image and Video Processing, 2019This study includes an evolutionary algorithm technique for sparse signal reconstruction in compressive sensing. In general, l1 minimization and greedy algorithms are used to reconstruct sparse signals. In addition to these methods, recently, heuristic algorithms have begun to be used to reconstruct sparse signals.
Murat Emre Erkoc, Nurhan Karaboga
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SIGNAL DROPOUT RECONSTRUCTION IN COMMUNICATING WITH CHAOS
International Journal of Bifurcation and Chaos, 2001A chaotic system can be guided by tiny perturbations to follow a previously chosen path in phase space carrying a desired sequence of binary symbols. We discuss how to exploit redundancy and flexibility of the chaotic carriers to reconstruct possible signal dropouts incurred in the communication channel, even in the case in which the receiver has no ...
Diego L. Valladares +3 more
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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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Reconstructing the Hippo signaling network
Science Bulletin, 2023Zhenxing, Zhong +2 more
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