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In this case, when improved data detection is obtained at the physical layer, together with an effective relay selection, a better system performance can be achieved.
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A second common feature is the use of feedback systems to improve data quality, though the error detection and correction approach varies across PHIT Partnerships.
Meanwhile, we use cooperative relays to improve data transmission quality [1] and constrain the probability of intercept and detection.
Furthermore, a one-step linear trend channel predictor is proposed to feed more accurate channel parameters to MMSE detector for improving the current data detection.
To reduce computational complexity of signal processing and improve performance of data detection, receiver structures that are matched to the physical channel characteristics are investigated.
Thus, a linear trend predictor is developed to predict one-step ahead channel for improving the performance of data detection in the following subsection.
Compared to conventional approaches, in addition to significantly improving the accuracy of data detection, the proposed JVSS algorithm can effectively perform signal frame synchronization because it fully exploits the structure of the baseband signals of RFID systems.
Although adding admission pNGAL to admission data improved early detection of AKI, this added value is lost upon inclusion of data from the first day of ICU.
On the other hand, data detection can be improved because refined channel estimates are obtained.
For data communication purpose, an iterative estimator for joint channel estimation and data detection with progressively improved accuracy is first proposed to achieve better performance of data communication.
We also observed that the single spike localization of MEEG data improved the detection accuracy of the sources at all eccentricities when compared to EEG or MEG localizations (Fig. 5).
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