2022
DOI: 10.3390/app122312176
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Deep Compressed Sensing Generation Model for End-to-End Extreme Observation and Reconstruction

Abstract: Data transmission and storage are inseparable from compression technology. Compressed sensing directly undersamples and reconstructs data at a much lower sampling frequency than Nyquist, which reduces redundant sampling. However, the requirement of data sparsity in compressed sensing limits its application. The combination of neural network-based generative models and compressed sensing breaks the limitation of data sparsity. Compressed sensing for extreme observations can reduce costs, but the reconstruction … Show more

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Cited by 5 publications
(3 citation statements)
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“…A generator network (G) and a discriminator network (D) make up the WGAN model, as seen in Figure 1 [32] [33]. An activation function (like sigmoid or tanh) is commonly used to normalize the output of the generator (G), which receives a random noise vector (z) as input that is typically sampled from a normal distribution.…”
Section: Generative Network Wgan Modelmentioning
confidence: 99%
“…A generator network (G) and a discriminator network (D) make up the WGAN model, as seen in Figure 1 [32] [33]. An activation function (like sigmoid or tanh) is commonly used to normalize the output of the generator (G), which receives a random noise vector (z) as input that is typically sampled from a normal distribution.…”
Section: Generative Network Wgan Modelmentioning
confidence: 99%
“…Nutation is a slight irregular motion of the axis in the precession of the rotation motion of the planet or gyroscope, which makes the rotation axis shake like a ' nod ' in the change of direction [16] , as shown in Figure 5. In this paper, the simple model B of IAU2000 nutation model is adopted, in which the time T represents the mechanical time starting from the J2000.0 standard epoch, taking the Julian century as the unit.…”
Section: Nutationmentioning
confidence: 99%
“…11 System model, the slices of the three letters of J, N and X in the figure can be regarded as images on three time frames. For this signal, this method realizes fast and high-resolution linear modulation and reconstruction of the central ROI region [16] .…”
Section: Simulation Experimentsmentioning
confidence: 99%