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One approach to evaluating the equalization performance is BER analysis, but it is generally quite complex.
These maps underwent whole-brain equalization for further statistical analysis [ 24, 25, 30].
The received symbols (after equalization) are stored for further analysis.
Theoretical analysis of the equalization problem reveals an inherent numerical deficiency, thus justifying our choice of employing a numerically robust algebraic transformation.
The automated method for pelvic CT bone segmentation is a hierarchical approach that combines filtering and histogram equalization, for image enhancement, wavelet analysis and automated seeded region growing.
We then derive a statistical performance analysis to compare the equalization performance with that of the optimal MMSE equalizer.
This paper concerns direct blind channel equalization using the programmable canonical correlation analysis (PCCA).
For instance, this happens in blind equalization and source separation, or spectral analysis [3, 4].
It is important to underline, that all the necessary synchronization, channel estimation and equalization operations take place after the analysis bank at the receiver, at the low sampling rate.
This article also tests the resistance of the precoding design to finite-sample estimation errors, and explores the effects of the precoding scheme on channel equalization by performing pairwise error probability analysis.
This study also tests the resistance of the precoding design to finite-sample estimation errors, and explores the effects of the precoding scheme on channel equalization through pairwise error probability (PEP) analysis.
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CEO of Professional Science Editing for Scientists @ prosciediting.com