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Practical signals in the various fields of engineering (telecommunications, acoustics, biomedical engineering) are nonstationary, with the instantaneous frequency (IF) being their key parameter [1].
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Due to the nonconvexity of the optimization problem, we propose suboptimum but practical signal processing schemes.
Moreover, they are not implementable unless they are supportable by practical signaling.
A non-linear trust-region algorithm is developed to fit the practical signal.
The authors believe that low oscillation complex wavelets have wide applicability to other practical signal analysis problems.
However, for a practical signal, Equation (2) is hard to solve due to the complexity of the signal autocorrelation.
The potential for cochannel interference mitigation through such joint processing is explored from a practical signal-processing standpoint in [15].
To carry out next comparisons, the standard denoising method is used in concern to actual data (Figures 7 and 8) related to practical signal presented.
Then, we try to modify the IA design in order to achieve enhanced sum-rate performance in the practical signal-to-noise ratio (SNR) region.
In this particular example, this happens in roughly 15 frames for the IA scheduler, both with practical signaling scheme and ideal interference CSI.
We will study transfer of information and also present some results on the practical signaling, reliability, and latency in such a multihop line network.
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