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中国科学：信息科学（英文版）
中国科学：信息科学（英文版）

周光召

月刊

1674-733X

informatics@scichina.org

010-64015683

100717

北京东黄城根北街16号

中国科学：信息科学（英文版）/Journal Science China Information SciencesCSCDCSTPCDEISCI
查看更多>>《中国科学》是中国科学院主办、中国科学杂志社出版的自然科学专业性学术刊物。《中国科学》任务是反映中国自然科学各学科中的最新科研成果，以促进国内外的学术交流。《中国科学》以论文形式报道中国基础研究和应用研究方面具有创造性的、高水平的和有重要意义的科研成果。在国际学术界，《中国科学》作为代表中国最高水平的学术刊物也受到高度重视。国际上最具有权威的检索刊物SCI，多年来一直收录《中国科学》的论文。1999年《中国科学》夺得国家期刊奖的第一名。
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    Multi-stream signals separation based on space-time-isomeric(SPATIO)array using metasurface antennas

    Yangming LOULiang JINHuiming WANGZhou ZHONG...
    177-196页
    查看更多>>摘要：In spatial domain signal processing,it is necessary to equip more antennas at the receiver to improve spatial demultiplexing capability.However,increasing the number of antennas under restricted space will reduce antenna spacing and raise the channel correlation,making the number of signal streams spatially demultiplexed much smaller than that of antennas.This paper proposes a method to design a space-time-isomeric(SPATIO)array based on metasurface antennas under wireless multipath conditions.Each antenna in this array has a different pattern and varies independently with time,reducing the channel correlation by superposing multipath at distinct positions and moments.Based on the SPATIO array,we present an array parameter design scheme based on infinity norm minimization,which can maximize the received energy of each stream while separating multi-stream received signals.Simulation results illustrate the performance of the SPATIO array for multi-stream signal reception.Compared with conventional multiple-input multiple-output arrays,the proposed array can reduce the bit error rate by one order of magnitude under the same simulation conditions.
      原文链接:
    • 万方数据
    • 维普

    Energy consumption optimization for edge computing-supported cellular networks based on optimal transport theory

    Xiangyu LVXiaohu GEYi ZHONGQiang LI...
    197-214页
    查看更多>>摘要：With advancements in mobile communication technologies,there have been multiple user device(UD)connections to cellular networks.Because of changes in the spatial distribution of UDs and application requirements,the traditional offloading mechanism based on the nearest distance will result in heavy loads for some base stations(BSs).Because there is a high-order relationship between the energy consumption of the BS processing tasks and the number of computing tasks,the traditional offloading mechanism will result in high energy consumption,and UD's offloading decision must be dynamically adjusted.The offloading decision of UDs is optimized based on detailed information about various parameters associated with a network from the standpoint of distribution.This information includes details regarding the spatial distribution of UDs,application requirements,and the offloading period of computing tasks.Based on optimal transport theory,an energy consumption optimization algorithm is suggested to lower the total amount of energy consumed by the offloading process of UDs'computing tasks by reasonably planning the offloading BSs of the UDs in the networks.The simulation results show that the proposed offloading mechanism based on energy consumption optimization reduces the total energy consumption of the offloading process by 28.09％when compared to the traditional offloading mechanism,and the traffic managed by each BS is balanced.
      原文链接:
    • 万方数据
    • 维普

    Analysis of phase preservation and interferometric offset test in sparse SAR imaging

    Zhongqiu XUBingchen ZHANGGuangzuo LIXueli ZHAN...
    215-227页
    查看更多>>摘要：Sparse synthetic aperture radar(SAR)imaging has emerged as a reliable microwave imaging scheme in the recent decade and excels in down-sampling reconstruction and full-sampling performance improvements such as noise,sidelobe,speckle,and ambiguity suppression.To utilize complex image products of sparse reconstruction for improvement in polarimetric,interferometric,and tomographic SAR imaging,it is necessary to evaluate the phase preservation of sparse SAR imaging.In this study,we first introduce the general alternating direction method of multipliers(ADMM)as the universal framework for sparse reconstruction algorithms and adopt chirp scaling algorithm(CSA)-based azimuth-range decouple operators to avoid expensive data storage and processing.Further,we theoretically analyze the phase preservation of the sparse reconstruction algorithm through a comparison with the reconstruction results of CSA.Finally,we conduct the interferometric offset test on the sparse reconstruction results of simulated and real Gaofen-3(GF-3)SAR data,demonstrating the phase-preserving ability of sparse methods.
      原文链接:
    • 万方数据
    • 维普

    Multiscale observation in wide-spatial radar surveillance based on coherent FDA design

    Lei YUFeng HEYi SU
    228-248页
    查看更多>>摘要：Wide-spatial radar surveillance missions are challenging tasks,requiring an increased power budget and agility in transmission aimed at extracting information from multiple targets in different en-vironments.These requirements necessitate high transmitting degrees of freedom(DOF)to achieve the objective of multiscale observation for specific tasks in specialized regions of interest.Herein,we exploit the multiscale observation ability in wide-spatial radar surveillance based on frequency diverse array(FDA)radar.The proposed method facilitates spatial anisotropic control of multiple radar resources,including the transmitting waveforms,beampattern,and bandwidth.By utilizing a coherent FDA radar,we offer principles for the selection of baseband waveforms,in addition to the quantitative design of the beampattern gain and optimal bandwidth from the perspective of detection.The feasibility of the proposed method is validated through numerical experiments,thus indicating the potential in wide-spatial radar surveillance.Moreover,this work can be regarded as a preliminary attempt to gauge the efficacy of the computational array,a novel academic concept.
      原文链接:
    • 万方数据
    • 维普

    FSS:algorithm and neural network accelerator for style transfer

    Yi LINGYujie HUANGYujie CAIZhaojie LI...
    249-262页
    查看更多>>摘要：Neural networks(NNs),owing to their impressive performance,have gradually begun to dom-inate multimedia processing.For resource-constrained and energy-sensitive mobile devices,an efficient NN accelerator is necessary.Style transfer is an important multimedia application.However,existing arbitrary style transfer networks are complex and not well supported by current NN accelerators,limiting their appli-cation on mobile devices.Moreover,the quality of style transfer needs improvement.Thus,we design the FastStyle system(FSS),where a.novel algorithm andan NN accelerator are proposed for style transfer.In FSS,we first propose a novel arbitrary style transfer algorithm,FastStyle.We propose a light network that contributes to high quality and low computational complexity and a prior mechanism to avoid retraining when the style changes.Then,we redesign an NN accelerator for FastStyle by applying two improvements to the basic NVIDIA deep learning accelerator(NVDLA)architecture.First,a flexible dat FSM and wt FSM are redesigned to enable the original data path to perform other operations(including the GRAM operation)by software programming.Moreover,statistics and judgment logic are designed to utilize the continuity of a video stream and remove the data dependency in the instance normalization,which improves the accelerator performance by 18.6％.The experimental results demonstrate that the proposed FastStyle can achieve higher quality with a lower computational cost,making it more suitable for mobile devices.The proposed NN ac-celerator is implemented on the Xilinx VCU118 FPGA under a 180-MHz clock.Experimental results show that the accelerator can stylize 512x512-pixel video with 20 FPS,and the measured performance reaches up to 306.07 GOPS.The ASIC implementation in TSMC 28 nm achieves about 22 FPS in the case of a 720-p video.
      原文链接:
    • 万方数据
    • 维普

    Geometry characteristics and wide temperature behavior of silicon-based GaN surface acoustic wave resonators with ultrahigh quality factor

    Guofang YURenrong LIANGHaiming ZHAOLei XIAO...
    263-274页
    查看更多>>摘要：Surface acoustic wave(SAW)resonators with an ultrahigh Q-factor are designed and fabricated on silicon-based gallium nitride(GaN/Si).The temperature-dependent performance is characterized over a wide range,from 10 to 500 K.Finite element analysis is employed to guide the design of the SAW resonator from indications of the Rayleigh mode and weak propagation direction dependence of SAW in the c-plane of GaN/Si.The SAW resonator with 100 pairs of interdigital transducers(IDT),100 pairs of grating reflectors(GR)for each side,aperture size of 80 pm,metallization ratio of 0.5,and electrode width of 500 nm resonates at 1.9133 GHz accordingly with an ultrahigh Q-factor of 7622 at room temperature,which contributes the fr × Qr,up to 14.583×1012 Hz.A resonator operating over 10 to 500 K indicates an approximately linear decreasing temperature dependence above 280 K while being approximately constant below 40 K.The fitting to resonator characteristics using the modified Butterworth Van Dyke(mBVD)model reveals a reduction in both the electrode and mechanical losses while worsening the dielectric loss with cooling down.
      原文链接:
    • 万方数据
    • 维普

    Experimental and numerical demonstration of hierarchical time-delay reservoir computing based on cascaded VCSELs with feedback and multiple injections

    Xingxing GUOShuiying XIANGXingyu CAOBiling GU...
    275-286页
    查看更多>>摘要：In this paper,we propose and demonstrate experimentally and numerically a hierarchical time-delay optical reservoir computing(RC)system based on cascaded vertical-cavity surface-emitting lasers(VCSELs)with feedback and multiple injections.The prediction performance characteristics of the hier-archical time-delay RC system based on cascaded VCSELs under different reservoir layers are compared.Evidently,the prediction performance of the hierarchical time-delay RC system is first improved and sat-urates as the number of reservoir layers increases.Besides,the impacts of key factors on predicting the hierarchical time-delay RC system are also analyzed in detail experimentally and numerically.This proposed hierarchical time-delay RC system based on VCSELs is useful for the further development of RC systems and may be beneficial to improve the ability of RC systems to solve more complex problems.
      原文链接:
    • 万方数据
    • 维普

    Investigation and mitigation of Mott neuronal oscillation fluctuation in spiking neural network

    Lindong WUZongwei WANGLin BAOLinbo SHAN...
    287-297页
    查看更多>>摘要：Mott devices,featuring low hardware cost and high energy efficiency,have been demonstrated as a key oscillatory element in artificial neurons to enable spiking neural networks(SNNs)such as conversion-based SNNs(CSNNs).However,there will be inevitably non-ideal fluctuation in the oscillation behavior,causing the accuracy degradation of networks.In this paper,we investigate the Mott neuronal oscillation fluctuation(NOF)through experiments and modeling.The results show that the NOF phenomenon conforms to Gaussian distribution and originates from thermal fluctuation induced switching voltage variations.We construct a two-layer CSNN for image recognition tasks to study the NOF effect and propose the activation function boundary(AFB)method to strengthen the stability of the network.The results indicate that AFB can improve the accuracy of CSNN by up to 15.5％by tightening output distribution.
      原文链接:
    • 万方数据
    • 维普

    SWG:an architecture for sparse weight gradient computation

    Weiwei WUFengbin TUXiangyu LIShaojun WEI...
    298-317页
    查看更多>>摘要：On-device training for deep neural networks(DNN)has become a trend due to various user preferences and scenarios.The DNN training process consists of three phases,feedforward(FF),backprop-agation(BP),and weight gradient(WG)update.WG takes about one-third of the computation in the whole training process.Current training accelerators usually ignore the special computation property of WG and process it in a way similar to FF/BP.Besides,the extensive data sparsity existing in WG,which brings opportunities to save computation,is not well explored.Nevertheless,exploiting the optimization opportunities would meet three underutilization problems,which are caused by(1)the mismatch between WG data dimensions and hardware parallelism,(2)the full sparsity,i.e.,the sparsity of feature map(Fmap),error map(Emap),and gradient,and(3)the workload imbalance resulting from irregular sparsity.In this paper,we propose a specific architecture for sparse weight gradient(SWG)computation.The architecture is designed based on hierarchical unrolling and sparsity-aware(HUSA)dataflow to exploit the optimization opportunities of the special computation property and full data sparsity.In HUSA dataflow,the data di-mensions are unrolled hierarchically on the hardware architecture.A valid-data trace(VDT)mechanism is embedded in the dataflow to avoid the underutilization caused by the two-sided input sparsity.The gradient is unrolled in PE to alleviate the underutilization induced by output sparsity while maintaining the data reuse opportunities.Besides,we design an intra-and inter-column balancer(IIBLC)to dynamically tackle the workload imbalance problem resulting from the irregular sparsity.Experimental results show that with HUSA dataflow exploiting the full sparsity,SWG achieves a speedup of 12.23× over state-of-the-art gradient computation architecture,TrainWare.SWG helps to improve the energy efficiency of the state-of-the-art training accelerator LNPU from 7.56 to 10.58 TOPS/W:
      原文链接:
    • 万方数据
    • 维普

    Optics-driven drone

    Xuelong LIGuan HUANGZhigang WANGBin ZHAO...
    318-320页
      原文链接:
    • 万方数据
    • 维普