Zobrazeno 1 - 10
of 105 221
pro vyhledávání: '"AN Zhenyu"'
Publikováno v:
Tongxin xuebao, Vol 45, Pp 170-182 (2024)
Due to the constraints of the satellite communication systems, the receiver signal processing was carried out in the time domain, which made traditional channel equalization algorithms face the challenge of high-dimensional matrix inversion. Taking f
Externí odkaz:
https://doaj.org/article/04a46885c8754cd6a533fca3c04acb15
In quantum learning tasks, quantum memory can offer exponential reductions in statistical complexity compared to any single-copy strategies, but this typically necessitates at least doubling the system size. We show that such exponential reductions c
Externí odkaz:
http://arxiv.org/abs/2410.17718
Approximate Nearest Neighbor (ANN) search in high-dimensional Euclidean spaces is a fundamental problem with a wide range of applications. However, there is currently no ANN method that performs well in both indexing and query answering performance,
Externí odkaz:
http://arxiv.org/abs/2411.14754
Generating high-quality stereo videos that mimic human binocular vision requires maintaining consistent depth perception and temporal coherence across frames. While diffusion models have advanced image and video synthesis, generating high-quality ste
Externí odkaz:
http://arxiv.org/abs/2411.14295
The application of deep learning (DL)-based channel state information (CSI) feedback frameworks in massive multiple-input multiple-output (MIMO) systems has significantly improved reconstruction accuracy. However, the limited generalization of widely
Externí odkaz:
http://arxiv.org/abs/2411.13298
Autor:
Wen, Zhenyu, Feng, Wanglei, Wu, Di, Hu, Haozhen, Xu, Chang, Qian, Bin, Hong, Zhen, Wang, Cong, Ji, Shouling
Federated Learning (FL), as a mainstream privacy-preserving machine learning paradigm, offers promising solutions for privacy-critical domains such as healthcare and finance. Although extensive efforts have been dedicated from both academia and indus
Externí odkaz:
http://arxiv.org/abs/2411.11713
Autor:
Wilks, Gavin, Ye, Zhenyu
A significant $\phi$-meson global spin alignment ($\rho_{00}$) signal was measured in Au+Au collisions at $\sqrt{s_{NN}}\le62$ GeV. Conventional physics mechanisms such as $s(\bar{s})$ spin polarization fail to accommodate this $\rho_{00}$ signal, mo
Externí odkaz:
http://arxiv.org/abs/2411.09782
The remarkable progress in neural-network-driven visual data generation, especially with neural rendering techniques like Neural Radiance Fields and 3D Gaussian splatting, offers a powerful alternative to GANs and diffusion models. These methods can
Externí odkaz:
http://arxiv.org/abs/2411.08642
Autor:
Alexeev, Yuri, Farag, Marwa H., Patti, Taylor L., Wolf, Mark E., Ares, Natalia, Aspuru-Guzik, Alán, Benjamin, Simon C., Cai, Zhenyu, Chandani, Zohim, Fedele, Federico, Harrigan, Nicholas, Kim, Jin-Sung, Kyoseva, Elica, Lietz, Justin G., Lubowe, Tom, McCaskey, Alexander, Melko, Roger G., Nakaji, Kouhei, Peruzzo, Alberto, Stanwyck, Sam, Tubman, Norm M., Wang, Hanrui, Costa, Timothy
Artificial intelligence (AI) advancements over the past few years have had an unprecedented and revolutionary impact across everyday application areas. Its significance also extends to technical challenges within science and engineering, including th
Externí odkaz:
http://arxiv.org/abs/2411.09131
Quark stars are challenging to confirm or exclude observationally because they can have similar masses and radii as neutron stars. By performing the first calculation of the non-equilibrium equation of state of decompressed quark matter at finite tem
Externí odkaz:
http://arxiv.org/abs/2411.09013