Results 31 to 40 of about 72,581 (258)
Weak Signal Detection Based on Combination of Sparse Representation and Singular Value Decomposition
Applied Sciences, 2022 Due to the inevitable acquisition system noise and strong background noise, it is often difficult to detect the features of weak signals. To solve this problem, sparse representation can effectively extract useful information according to the sparse ...
Huijie Ma +3 more
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Concentration measures with an adaptive algorithm for processing sparse signals [PDF]
2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA), 2013 In the L-estimation and compressive sensing some arbitrarily positioned samples of the signal are either so heavily corrupted by disturbances that it is better to omit them in the analysis or they are unavailable. If the considered signal with missing samples is sparse then we are still able to reconstruct these samples by using the well know ...
Ljubisa Stankovic +2 more
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Filtered Variation method for denoising and sparse signal processing [PDF]
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012 We propose a new framework, called Filtered Variation (FV), for denoising and sparse signal processing applications. These problems are inherently ill-posed. Hence, we provide regularization to overcome this challenge by using discrete time filters that are widely used in signal processing.
Kivanç Köse +2 more
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Deep Learning Meets Sparse Regularization: A signal processing perspective
IEEE Signal Processing Magazine, 2023 Deep learning has been wildly successful in practice and most state-of-the-art machine learning methods are based on neural networks. Lacking, however, is a rigorous mathematical theory that adequately explains the amazing performance of deep neural networks.
Rahul Parhi, Robert D. Nowak
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The application of sparse linear prediction dictionary to compressive sensing in speech signals
上海师范大学学报. 自然科学版, 2016 Appling compressive sensing (CS),which theoretically guarantees that signal sampling and signal compression can be achieved simultaneously,into audio and speech signal processing is one of the most popular research topics in recent years.In this paper,K ...
YOU Hanxu, LI Wei, LI Xin, ZHU Jie
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International Journal of Distributed Sensor Networks, 2020 Sparse decomposition has excellent adaptability and high flexibility in describing arbitrary complex signals based on redundant and over-complete dictionary, thus having the advantage of being free from the limitations of traditional signal processing ...
Hongchao Wang, Wenliao Du
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Sub-Nyquist sampling of sparse and correlated signals in array processing
Digital Signal Processing, 2023 This paper considers efficient sampling of simultaneously sparse and correlated (S$\&$C) signals. Such signals arise in various applications in array processing. We propose an implementable sampling architecture for the acquisition of S$\&$C at a sub-Nyquist rate.
Ali Ahmed 0004 +2 more
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Natural Killer Cells in Paediatric Soft Tissue Sarcomas: A Systematic Review
Pediatric Blood &Cancer, EarlyView.ABSTRACT Paediatric soft tissue sarcomas (pSTS) are a rare and heterogeneous group of malignant tumours arising in tissues of mesenchymal origin. The role of natural killer (NK) cells in pSTS remains poorly understood, with evidence fragmented across small preclinical studies and early‐phase clinical trials.
Raya Dean +7 more
wiley +1 more source
Construction Method of Sparse Dictionary for Multi-Order FRFT Domain Feature Fusion
Archives of AcousticsReverberation constitutes a primary source of interference for active sonar signals, particularly the intense reverberation originating from reflections of the incident signal. Sharing the same generation mechanism as the target echo, it severely hampers
Tongjing Sun, Lei Chen, Xiaohong Deng
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Remote Sensing, 2019 The magnetic resonance sounding (MRS) method is a non-invasive, efficient and advanced geophysical method for groundwater detection. However, the MRS signal received by the coil sensor is extremely susceptible to electromagnetic noise interference.
Xiaokang Yao +4 more
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