Results 321 to 330 of about 28,422,071 (389)
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Filling the Data Gaps Within GRACE Missions Using Singular Spectrum Analysis
Journal of Geophysical Research: Solid Earth, 2021Dozens of missing epochs in the monthly gravity product of the satellite mission Gravity Recovery and Climate Experiment (GRACE) and its follow‐on (GRACE‐FO) mission greatly inhibit the complete analysis and full utilization of the data. Despite previous
S. Yi, N. Sneeuw
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Temporal-Spatio Graph Based Spectrum Analysis for Bearing Fault Detection and Diagnosis
IEEE transactions on industrial electronics (1982. Print), 2021This article suggests that the correlation information, hidden in spatial configuration and temporal dynamic of frequencies, is an important indication for bearing health condition.
Teng Wang +3 more
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An approach for wheel flat detection of railway train wheels using envelope spectrum analysis
Structure and Infrastructure Engineering, 2020Due to the increasing demand for safer and faster rail transport, train wheelsets operating under high axle loads require more careful and reliable inspections and maintenance.
A. Mosleh +3 more
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IEEE Sensors Letters, 2020
In this letter, the multivariate automatic singular spectrum analysis (MA-SSA) and multivariate sliding-mode singular spectrum analysis (MSM-SSA) algorithms are proposed as multivariate extensions to automatic singular spectrum analysis and sliding-mode ...
Sahil Jain, Rohan Panda, R. Tripathy
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In this letter, the multivariate automatic singular spectrum analysis (MA-SSA) and multivariate sliding-mode singular spectrum analysis (MSM-SSA) algorithms are proposed as multivariate extensions to automatic singular spectrum analysis and sliding-mode ...
Sahil Jain, Rohan Panda, R. Tripathy
semanticscholar +1 more source
Spectrum Analysis and Convolutional Neural Network for Automatic Modulation Recognition
IEEE Wireless Communications Letters, 2019Recent convolutional neural networks (CNNs)-based image processing methods have proven that CNNs are good at extracting features of spatial data. In this letter, we present a CNN-based modulation recognition framework for the detection of radio signals ...
Yuan Zeng +4 more
semanticscholar +1 more source
2022
AbstractThe analysis of random processes requires a thorough understanding of spectrum and noise analysis. In Chapter 6, Fourier transforms for deterministic and stochastic time series are presented, with application to spectrum analysis. The spectrum analysis for stochastic signal is presented with application to white and coloured noise. The Singular
Marco Bittelli +2 more
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AbstractThe analysis of random processes requires a thorough understanding of spectrum and noise analysis. In Chapter 6, Fourier transforms for deterministic and stochastic time series are presented, with application to spectrum analysis. The spectrum analysis for stochastic signal is presented with application to white and coloured noise. The Singular
Marco Bittelli +2 more
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Geophysics, 2019
We have evaluated a fast and memory efficient implementation of the multidimensional singular spectrum analysis (MSSA) method for seismic data reconstruction. The new algorithm makes use of random projections and the structure of Hankel matrices to avoid
Jinkun Cheng, M. Sacchi, Jianjun Gao
semanticscholar +1 more source
We have evaluated a fast and memory efficient implementation of the multidimensional singular spectrum analysis (MSSA) method for seismic data reconstruction. The new algorithm makes use of random projections and the structure of Hankel matrices to avoid
Jinkun Cheng, M. Sacchi, Jianjun Gao
semanticscholar +1 more source
Adaptive singular spectrum analysis for seismic denoising and interpolation
Geophysics, 2019We have developed an adaptive singular spectrum analysis (ASSA) method for seismic data denoising and interpolation purposes. Our algorithm iteratively updates the singular-value decomposition (SVD) of current spatial patches using the most recently ...
Hojjat Haghshenas Lari +3 more
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2003
All electrical signals can be described either as a function of time or of frequency. When we observe signals as a function of time they are called the time domain measurements. Sometimes, we observe the frequencies present in signals, in which case they are called the frequency domain measurements.
Kularatna, N., Hettiwatte, S.N.
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All electrical signals can be described either as a function of time or of frequency. When we observe signals as a function of time they are called the time domain measurements. Sometimes, we observe the frequencies present in signals, in which case they are called the frequency domain measurements.
Kularatna, N., Hettiwatte, S.N.
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Spectrum Analysis of the Stream Cipher
Applied Mechanics and Materials, 2012Classical cryptography theory holds that the true random sequence is better than any pseudorandom sequence on the security of stream cipher. So people prefer the pseudorandom sequence with long-period to the pseudorandom sequence with short-period. In this paper, it is proved through power spectrum analysis that the pseudorandom sequence with long ...
null Daimao Lin +2 more
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