Results 41 to 50 of about 2,854,386 (335)
Adaptive Processing With Signal Contaminated Training Samples
IEEE Transactions on Signal Processing, 2013 We consider the adaptive beamforming or adaptive detection problem in the case of signal contaminated training samples, i.e., when the latter may contain a signal-like component. Since this results in a significant degradation of the signal to interference and noise ratio at the output of the adaptive filter, we investigate a scheme to jointly detect ...
Besson, Olivier, Bidon, Stéphanie
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Experimental Study on Sampling Theorem in Signal Processing
Journal La Multiapp, 2021 This practicum is to define the study properties of the sampling theorem. Understand the effect of selecting the sample size and its effect on the signal recovery process. The experiment utilizes a computer or portable workstation to run an examination of the hypothesis reenactment program. From the test information gotten, it can be concluded that the
Nyein Mynt, Kyaw Lin, Zaw Aung
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Imaging Method for Co-prime-sampling Space-borne SAR Based on 2D Sparse-signal Reconstruction
Leida xuebao, 2020 Co-prime-sampling space-borne Synthetic Aperture Radar (SAR) replaces the traditional uniform sampling by performing co-prime sampling in azimuth, which effectively alleviates the conflict between spatial resolution and effective swath width, while also
ZHAO Wanwan +3 more
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Phased Fractional Lower-Order Cyclic Moment Processed in Compressive Signal Processing
IEEE Access, 2019 In signal processing research, cyclostationarity and fractional lower-order statistics (FLOS) are two important solutions to non-stationary signals and non-Gaussian noises, respectively.
Tao Liu +4 more
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TERRESTRIAL LASER SCANNER DATA DENOISING BY DICTIONARY LEARNING OF SPARSE CODING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 Point cloud processing is basically a signal processing issue. The huge amount of data which are collected with Terrestrial Laser Scanners or photogrammetry techniques faces the classical questions linked with signal or image processing.
E. Smigiel, E. Alby, P. Grussenmeyer
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Near-Optimal Graph Signal Sampling by Pareto Optimization
Sensors, 2021 In this paper, we focus on the bandlimited graph signal sampling problem. To sample graph signals, we need to find small-sized subset of nodes with the minimal optimal reconstruction error.
Dongqi Luo +4 more
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Evaluating graph signal processing for neuroimaging through classification and dimensionality reduction [PDF]
IEEE Global Conference on Signal and Information Processing, 2017 Graph Signal Processing (GSP) is a promising framework to analyze multi-dimensional neuroimaging datasets, while taking into account both the spatial and functional dependencies between brain signals.
M. Ménoret +3 more
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Frontiers in Neurology, 2015 We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion gradient directions for high angular resolution diffusion magnetic resonance imaging.
Farshid eSepehrband +12 more
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Engineering Proceedings, 2023 The complex and changing underwater environment, along with the presence of various suspended particles, leads to laser attenuation and backward scattering. As a result, the detection capabilities of underwater LiDAR are significantly limited. To address
Guangbo Xu
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Adaptive Rate Sampling and Filtering Based on Level Crossing Sampling
EURASIP Journal on Advances in Signal Processing, 2009 The recent sophistications in areas of mobile systems and sensor networks demand more and more processing resources. In order to maintain the system autonomy, energy saving is becoming one of the most difficult industrial challenges, in mobile computing.
Saeed Mian Qaisar +2 more
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