Results 21 to 30 of about 3,600,645 (297)
Blind source separation algorithm for complex signals in noise
Dianzi Jishu Yingyong, 2022 Complex signal analysis is one of the common problems in signal processing technology. In blind signal separation technology, especially convolution mixing problem or frequency domain analysis, it is necessary to establish the corresponding complex value
Feng Pingxing, Zhang Hongbo, Li Wenxiang
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On the Optimal Recovery of Graph Signals
2023 International Conference on Sampling Theory and Applications (SampTA), 2023 Learning a smooth graph signal from partially observed data is a well-studied task in graph-based machine learning. We consider this task from the perspective of optimal recovery, a mathematical framework for learning a function from observational data that adopts a worst-case perspective tied to model assumptions on the function to be learned. Earlier
Simon Foucart, Chunyang Liao, Nate Veldt
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Sketching and Stacking With Random Fork Based Exact Signal Recovery Under Sample Corruption
IEEE Access, 2020 In this paper, we propose a new technique for exact recovery of missing data due to impulsive noise in time-domain sampled acoustic waves, named as sketching and stacking with random fork (SSRF).
Joo Hyun Park +3 more
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IEEE Open Journal of Antennas and Propagation, 2021 We propose an innovative approach to the phase retrieval of 2-D discrete complex signals. The solution strategy profitably exploits some fundamental results available for the phase retrieval of one-dimensional discrete signals by following a simple yet ...
G. M. Battaglia +4 more
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Dualization of Signal Recovery Problems [PDF]
Set-Valued and Variational Analysis, 2010 In convex optimization, duality theory can sometimes lead to simpler solution methods than those resulting from direct primal analysis. In this paper, this principle is applied to a class of composite variational problems arising in particular in signal recovery.
Combettes, Patrick L. +2 more
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Dilated POCS: Minimax Convex Optimization
IEEE Access, 2023 Alternating projection onto convex sets (POCS) provides an iterative procedure to find a signal that satisfies two or more convex constraints when the sets intersect.
Albert R. Yu +6 more
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Methods for early recognition of OFDM data [PDF]
Компьютерная оптика, 2020 A technique of early recognition (recovery) of data transmitted using OFDM technology by an incompletely received signal is considered. Theoretically, this approach is able to increase the speed of information transfer, as well as the resistance of the ...
Ruslan Yuzkiv +3 more
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Entropy, 2023 Compressive sensing is a sub-Nyquist sampling technique for efficient signal acquisition and reconstruction of sparse or compressible signals. In order to account for the sparsity of the underlying signal of interest, it is common to use sparsifying ...
Mohammad Shekaramiz, Todd K. Moon
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Sampling and Recovery of Graph Signals [PDF]
, 2018 The aim of this chapter is to give an overview of the recent advances related to sampling and recovery of signals defined over graphs. First, we illustrate the conditions for perfect recovery of bandlimited graph signals from samples collected over a selected set of vertexes. Then, we describe some sampling design criteria proposed in the literature to
Paolo Di Lorenzo +2 more
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Sparse signal recovery with unknown signal sparsity [PDF]
EURASIP Journal on Advances in Signal Processing, 2014 In this paper, we proposed a detection-based orthogonal match pursuit (DOMP) algorithm for compressive sensing. Unlike the conventional greedy algorithm, our proposed algorithm does not rely on the priori knowledge of the signal sparsity, which may not be known for some application, e.g., sparse multipath channel estimation.
Wenhui Xiong, Jin Cao, Shaoqian Li
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