ID 原文 译文
56418 基于65 nm CMOS体硅工艺,所实现的Ka频段CMOS相控阵芯片噪声系数为3.0 d B,发射通道效率为15%,无需校准即可实现精确幅相控制,相关测试结果表明所研制的低成本相控阵芯片具有集成度高、幅相控制精确等优势,噪声系数等关键技术指标接近砷化镓工艺. Fabricated in 65 nm bulk CMOS, the proposed Ka-band phased-array ICs achieve 3. 0 dB noise figure, 15% PAE,and accurate amplitude and phase controls without calibration. The CMOS ICs outperform GaAs ICs in termsof integration and cost. Measurement results show that the key performance metrics (e. g. , noise figure) of thiswork are close to that of GaAs ICs.
56419 以此为基础,本文给出了基于多层混压PCB工艺的1024发射/1024接收超大规模"集成相控阵"设计技术,并将其扩展至4096发射/4096接收相控阵规模,最后给出了低成本、高集成宽带卫星移动通信终端在车载和船载条件下的示范应用结果. Based on the proposed CMOS phased-array ICs, the design of 1024 TX/1024RX large-scale integrated phased-array antennas is realized in PCB technology, which are further extended tothe scale of 4096 TX/4096 RX phased-array antennas. Finally, vehicle-mounted and shipboard tests are per?formed using the proposed low-cost and high-integration phased-array antenna terminal for broadband satellitecommunications.
56420 在神经美学研究中已经证明,中文字体审美偏好的情绪刺激可以通过观察3种偏好(喜欢、不喜欢和中性)之间的事件相关电位(event related potential, ERP)波动获得. Previous neuroesthetic studies have proved that Chinese typefaces can be viewed as an esthetic preference stimulus by observing differences in event related potential (ERP) waves among three preferences,namely, like, dislike, and neutral.
56421 本文通过引入一种核化张量奇异值分解的多视角聚类方法分别构建了基于脑电图(electroencephalogram, EEG)和ERP的审美偏好识别模型,通过这些模型首次确认了该结论. We first reconfirm this conclusion by introducing a multiview clustering methodof kernelized tensor singular value decomposition (KT-SVD) to construct an esthetic preference recognition model based on electroencephalograms (EEGs).
56422 本文方法将来自不同频段的数据视为描述中文字体审美偏好的不同视角,通过张量多秩最小化的约束探索所有视角特征的一致性和关联性,并通过之后的聚类获取审美偏好的识别结果.采用多视角无监督聚类方法得到的识别精度达到97. Our approach regards data from different frequency bands as different views describing the esthetic preferences of Chinese fonts, explore the relevance of all view features through the constraint of tensor multi-rank minimization, and obtains the esthetic preferences using the clustering results.
56423 1%.此外,通过输入–扰动关联方法将电极的振幅与不同种类的审美偏好相关联,可视化关键频段组合以及电极之间的关系,分别取出与喜欢、不喜欢、中性最相关的3个电极,包含次相关的6个电极,包含第三相关的9个电极,包含第四相关的12个电极,分别形成4种不同组合的脑电特征.通过比较实验,验证了相对于62个电极信号,上述4种组合方式在字体美学分类上更具有优势,并且最相关的3个电极的组合特征对审美偏好最具判别性. Additionally, the input-perturbation correlation method is used to correlate the amplitude of the electrodes with different types of esthetic preferences and describe the relationship between the key frequency-band combinations and electrodes, and take out the electrodes most relevant to likes, dislikes, and neutrality, including 3 electrodes of Top-1, 6 electrodes of Top-2, 9 electrodes of Top-3, and 12 electrodes of Top-4, forming four different combinationsof EEG features for esthetic preference recognition experiments.
56424 实验结果表明,基于多视角聚类的方法能够解决神经信号与审美偏好的相关分析,并能挖掘出与字体审美偏好最相关的电极 Experimental results show that the method based on multiview clustering can solve the correlation analysis of neural signals and esthetic preferences and mine the electrodes most relevant to the esthetic preferences of fonts.
56425 随着应用数据处理需求的激增,在传统冯·诺依曼(von Neumann)体系结构中,处理器到主存之间的总线数据传输逐渐成为瓶颈. With the explosive increase of processed data, data transmission through the bus between CPUand the main memory has become a bottleneck in the traditional von Neumann architecture.
56426 不仅如此,近年来兴起的数据密集型应用,如神经网络和图计算等,呈现出较严重的数据局部性,缓存命中率低. On top of this,popular data-intensive workloads, such as neural networks and graph computing applications, have poor datalocality, which results in a substantial increase of the cache miss rate.
56427 在这些新兴数据密集型应用的处理过程中,中央处理器到主存间的数据传输量大,导致系统的性能不佳且能耗变高. Processing such popular data-intensiveworkloads hinders the entire system since the data transmission causes long latency and high energy consumption.