Zobrazeno 1 - 10
of 634
pro vyhledávání: '"Deep Unfolding"'
Autor:
Yuya Kawamura, Satoshi Takabe
Publikováno v:
IEEE Access, Vol 12, Pp 177911-177918 (2024)
Stein variational gradient descent (SVGD) is a prominent particle-based variational inference method used for sampling a target distribution. In this paper, we propose two novel trainable algorithms based on SVGD: deep-unfolded SVGD (DUSVGD) and Cheb
Externí odkaz:
https://doaj.org/article/67c2c906e3ec407ca2a1a065b1024b61
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 6697-6712 (2024)
Monostatic backscatter has garnered significant interest due to its distinct benefits in low-cost passive sensing. Observing and sensing with backscatter necessitates determining the phase and amplitude of the backscatter channel to identify the stat
Externí odkaz:
https://doaj.org/article/f56838aa5a6444ca8926c1e06ab14b0a
Publikováno v:
IEEE Photonics Journal, Vol 16, Iss 4, Pp 1-10 (2024)
Single-pixel imaging (SPI), an imaging technique based on the theory of compressed sensing, is limited in real-time imaging and high-resolution images due to its relatively slow imaging speed. In recent years, deep unfolding network compressed sensin
Externí odkaz:
https://doaj.org/article/a01365a4697c469ab2b700f77db16fe9
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 3753-3761 (2024)
In-band full-duplex (IBFD) can double the spectral efficiency of wireless communications systems. However, its major drawback is the self-interference, which interferes with the desired signal at the terminal. Self-interference cancelation can be ope
Externí odkaz:
https://doaj.org/article/912fb43370d44b7e97ab3ffade864fdf
Publikováno v:
IEEE Access, Vol 12, Pp 76663-76672 (2024)
In this paper, an intelligent reflecting surface (IRS)-assisted integrated sensing and communication (ISAC) system is considered, where the ISAC base station (BS) serves the communication user equipments (UEs) and tracks sensing targets simultaneousl
Externí odkaz:
https://doaj.org/article/6f87f69ce0854cc6b0a7dfc7b66917aa
Autor:
Haitao Yin, Hao Chen
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 4125-4138 (2024)
Despite the significant successes in hyperspectral image (HSI) denoising, pure data-driven HSI denoising networks still suffer from limited understanding of inference. Deep unfolding (DU) is a feasible way to improve the interpretability of deep netw
Externí odkaz:
https://doaj.org/article/a64d117c91ac47ad85b4282a042798bc
Publikováno v:
IEEE Photonics Journal, Vol 16, Iss 1, Pp 1-9 (2024)
Sparse-viewcomputed tomography (CT) imaging is a promising technique for reducing radiation dose and accelerating data acquisition in medical imaging. However, the challenges of handling a reduced number of projection views persist for both iterative
Externí odkaz:
https://doaj.org/article/b60c7555477242c188e1c82602834508
Publikováno v:
Sensors, Vol 24, Iss 19, p 6184 (2024)
Recently, deep unfolding network methods have significantly progressed in hyperspectral snapshot compressive imaging. Many approaches directly employ Transformer models to boost the feature representation capabilities of algorithms. However, they oft
Externí odkaz:
https://doaj.org/article/c30c40f0eb564b7c86eb429b2ebc62ce
Publikováno v:
Remote Sensing, Vol 16, Iss 14, p 2516 (2024)
Space–time adaptive processing (STAP) based on sparse recovery achieves excellent clutter suppression and target detection performance, even with a limited number of available training samples. However, most of these methods face performance degrad
Externí odkaz:
https://doaj.org/article/07a21027109e40849c93a24011f3f11f
Publikováno v:
Sensors, Vol 24, Iss 14, p 4574 (2024)
Recently, the low-rank representation (LRR) model has been widely used in the field of remote sensing image denoising due to its excellent noise suppression capability. However, those low-rank-based methods always discard important edge details as re
Externí odkaz:
https://doaj.org/article/a8ff4069d1ce4224a9289d119b1c6b3a