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In order to produce a high amount of vibration signals, considering different defect dimensions and noise levels, the BEAring Toolbox (BEAT) is employed in this work.
This study also provides an insight into how to select a reference channel for the CC technique with EEG signals considering the anatomical structure of the human brain.
Then, in order to overcome the interference of the two pilot signals, considering the channel orders known, the CSI of the individual channels between each user and the relay are identified.
In this paper we study the detection problem of MCM signals considering the AWGN and Rayleigh fading environment by using an induced cyclostationary scheme [20], which is realized by intentionally embedding some cyclostationary signatures.
Mauri et al. [ 13] excluded some diaphragmatic signals, considering them as artifacts, in their study.
Expression measures for each probeset were obtained using GCRMA [ 110], which is a multi-array analysis method estimating probeset signals considering the physical affinities between probes and targets.
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Signals considered in this paper mostly contain swallowing vibrations.
The variables A and f k are constant as the signals considered are PSK signals.
Theorem 3.4 (Exact recovery for cosparse signals) Consider the problem p when ‖e‖2 = 0.
The additive noise signals considered here do not vanish at the equilibrium and the uncertainties are norm bounded.
Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults.
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