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The ZF solution can be obtained from the MMSE solution by setting the signal power to infinity.
A parametric dataset was created from DIFF by setting the signal in voxels belonging to Cl3 and Cl4 to zero.
The simulated artifacts were created by inserting a spherical volume into the image and setting the signal to 0 within the volume.
The reference SNRrx denotes the amount of noise power by setting the signal power with a 50% dimming level as the reference signal power.
The open source software framework GNU radio under GNU general public license (GPL) was adopted to realize the transceiver chain depicted in Fig. 4. The choice of GNU radio was motivated by its scalability, its flexibility in setting the signal processing components, and its wide user base.
All images were background corrected setting the signal outside the hyphae to zero to obtain a sufficiently dark background.
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An additive white Gaussian noise was added to the system output, setting the signal-to-noise ratio (SNR) to 30 dB. Figure 4 compares the convergence of the NSAF, SR-NSAF, and MSR-NSAF algorithms with N = 4 for different step sizes (1, 0.2, and 0.05).
The pulse blanking method mitigates the interference by setting the signals which exceed the threshold to zero in time domain.
Likewise, we will disable the measurement of these image parts, by setting the signals, and to zero.
Pulse blanking method mitigates the interference by setting the signals which exceed the threshold to zero in time domain [5, 6].
We also set the signal x with the even block size and the total sparsity k 0 = 64.
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