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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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    Memory-enhanced text style transfer with dynamic style learning and calibration

    Fuqiang LINYiping SONGZhiliang TIANWangqun CHEN...
    177-192页
    查看更多>>摘要：Text style transfer aims to rephrase a sentence to match the desired style while retaining the original content.As a controllable text generation task,mainstream approaches use content-independent style embedding as control variables to guide stylistic generation.Nonetheless,stylistic properties are context-sensitive even under the same style.For example,"delicious"and"helpful"convey positive sentiments,although they are more likely to describe food and people,respectively.Therefore,desired style signals must vary with the content.To this end,we propose a memory-enhanced transfer method,which learns fine-grained style representation concerning content to assist transfer.Rather than employing static style embedding or latent variables,our method abstracts linguistic characteristics from training corpora and memorizes subdivided content with the corresponding style representations.The style signal is dynamically retrieved from memory using the content as a query,providing a more expressive and flexible latent style space.To address the imbalance between quantity and quality in different content,we further introduce a calibration method to augment memory construction by modeling the relationship between candidate styles.Experimental results obtained using three benchmark datasets confirm the superior performance of our model compared to competitive approaches.The evaluation metrics and case study also indicate that our model can generate diverse stylistic phrases matching context.
      原文链接:
    • 万方数据
    • 维普

    A model reduction approach for discrete-time linear time-variant systems with delayed inputs

    Ai-Guo WUGuang-Ren DUANYu WANGJie ZHANG...
    193-213页
    查看更多>>摘要：A model reduction approach is presented for discrete-time linear time-variant input-delayed systems.According to this proposed approach,a dynamical variable is constructed by taking advantage of the current state and historical information of input.It is revealed that the behavior of this dynamical variable is governed by a discrete-time linear delay-free system.It is worth noting that the presented variable transformation does not require the system matrix to be invertible.Based on the reduced delay-free models,stabilizing control laws can be easily obtained for the original delayed system.For the case with a single input delay,the constructed variable is an exact prediction for the future state,and thus the stabilizing control law could be designed by replacing the future state with its prediction.Finally,three discrete-time periodic systems with delayed input are employed to illustrate how to utilize the presented model reduction approaches.
      原文链接:
    • 万方数据
    • 维普

    Higher-order properties and extensions for indirect MR AC and APPC of linear systems

    Yanjun ZHANGZhipeng ZHANGJian SUNLei WANG...
    214-234页
    查看更多>>摘要：Recently,a reference derived some new higher-order output tracking properties for direct model reference adaptive control(MRAC)of linear time-invariant(LTI)systems:limt→∞ e(i)(t)=0,i=1,…,n*-1,where n*and e(i)(t)denote the relative degree of the system and the i-th derivative of the output tracking error,respectively.However,a naturally arising question involves whether indirect adaptive control(including indirect MRAC and indirect adaptive pole placement control)of LTI systems still has higher-order tracking properties.Such properties have not been reported in the literature.Therefore,this paper provides an affirmative answer to this question.Such higher-order tracking properties are new discoveries since they hold without any additional design conditions and,in particular,without the persistent excitation condition.Given the higher-order properties,a new adaptive control system is developed with stronger tracking features.(1)It can track a reference signal with any order derivatives being unknown.(2)It has higher-order exponential or practical output tracking properties.(3)Finally,it is different from the usual MRAC system,whose reference signal's derivatives up to the n*order are assumed to be known.Finally,two simulation examples are provided to verify the theoretical results obtained in this paper.
      原文链接:
    • 万方数据

    On the size generalizibility of graph neural networks for learning resource allocation

    Jiajun WUChengjian SUNChenyang YANG
    235-250页
    查看更多>>摘要：Size generalization is important for learning resource allocation policies in wireless systems with time-varying scales.If a neural network for learning a wireless policy is not generalizable to the size of its input,it has to be re-trained whenever the system scale changes,which hinders its practical use due to the unaffordable training costs.Graph neural networks(GNNs)have been shown with size generalization ability empirically when optimizing resource allocation.Yet,are GNNs naturally size generalizable?In this paper,we argue that GNNs are not always size generalizable for resource allocation.We find that the aggregation and activation functions of the GNNs for learning a class of wireless policies play a key role in their size generalization ability.We take the GNN with the mean aggregator,called mean-GNN,as an example to reveal a size generalization condition.To demonstrate how to satisfy the condition,we learn power and bandwidth allocation policies for ultra-reliable low-latency communications and show that selecting or pre-training the activation function in the output layer of mean-GNN can make the GNN size generalizable.Simulation results validate our analysis and evaluate the performance of the learned policies.
      原文链接:
    • 万方数据
    • 维普

    Impact of non-ideal UE hardware on cell-free massive MIMO network with centralized operation

    Ning LIPingzhi FAN
    251-267页
    查看更多>>摘要：This paper investigates the impact of non-ideal user equipment(UE)hardware on a cell-free(CF)massive MIMO(mMIMO)network with centralized operation under spatially correlated channels.The minimum mean-squared error(MMSE)estimator can be derived with the help of the generic non-ideal UE hardware model.It is demonstrated that even if the effective signal-to-noise ratio approaches infinity,pilot contamination and imperfect hardware can cause a non-zero estimation error floor.After that,a lower bound is determined for the ergodic uplink capacity of the centralized CF mMIMO network under non-ideal UE hardware.Moreover,the optimal receive combining vector is obtained to maximize the uplink spectral efficiency(SE).The maximum ratio(MR)and regularized zero-forcing(RZF)combining schemes are offered as alternatives in light of the computational complexity of the MMSE receiver.Comparing the RZF to the MMSE scheme under different levels of hardware impairments,our findings indicate that the RZF receiver suffers a negligible loss in total SE.For MR combining,a novel closed-form uplink achievable SE expression is obtained based on the MMSE estimator and the use-and-then-forget bounding technique.This expression gives vital insights into the achievable uplink performance with UE hardware impairments.Besides,for various hardware impairment factors,the impact of pilot sequence length on average sum SE is disclosed for different receive combining schemes.To increase the overall SE of the max-min fairness scheme,a heuristic fractional power control scheme with UE hardware impairments is developed,which can essentially avoid sacrificing the SE of other UEs while maximizing the SE of the unluckiest UE in the whole network.Finally,our theoretical performance analysis and power control algorithm are validated by simulation results,and fundamental design guidelines are provided for selecting hardware satisfying the practical UE requirements.
      原文链接:
    • 万方数据
    • 维普

    Gradient sparsification for efficient wireless federated learning with differential privacy

    Kang WEIJun LIChuan MAMing DING...
    268-284页
    查看更多>>摘要：Federated learning(FL)enables distributed clients to collaboratively train a machine learning model without sharing raw data with each other.However,it suffers from the leakage of private informa-tion from uploading models.In addition,as the model size grows,the training latency increases due to the limited transmission bandwidth and model performance degradation while using differential privacy(DP)protection.In this paper,we propose a gradient sparsification empowered FL framework with DP over wire-less channels,to improve training efficiency without sacrificing convergence performance.Specifically,we first design a random sparsification algorithm to retain a fraction of the gradient elements in each client's local model,thereby mitigating the performance degradation induced by DP and reducing the number of transmission parameters over wireless channels.Then,we analyze the convergence bound of the proposed algorithm,by modeling a non-convex FL problem.Next,we formulate a time-sequential stochastic optimiza-tion problem for minimizing the developed convergence bound,under the constraints of transmit power,the average transmitting delay,as well as the client's DP requirement.Utilizing the Lyapunov drift-plus-penalty framework,we develop an analytical solution to the optimization problem.Extensive experiments have been implemented on three real-life datasets to demonstrate the effectiveness of our proposed algorithm.We show that our proposed algorithms can fully exploit the interworking between communication and computation to outperform the baselines,i.e.,random scheduling,round robin,and delay-minimization algorithms.
      原文链接:
    • 万方数据
    • 维普

    Post-layout simulation driven analog circuit sizing

    Xiaohan GAOHaoyi ZHANGSiyuan YEMingjie LIU...
    285-296页
    查看更多>>摘要：Post-layout simulation provides accurate guidance for analog circuit design,but post-layout performance is hard to be directly optimized at early design stages.Prior work on analog circuit sizing often utilizes pre-layout simulation results as the optimization objective.In this work,we propose a post-layout-simulation-driven(post-simulation-driven for short)analog circuit sizing framework that directly optimizes the post-layout simulation performance.The framework integrates automated layout generation into the optimization loop of transistor sizing and leverages a coupled Bayesian optimization algorithm to search for the best post-simulation performance.Experimental results demonstrate that our framework can achieve over 20％better post-layout performance in competitive time than manual design and the method that only considers pre-layout optimization.
      原文链接:
    • 万方数据
    • 维普

    Quantum self-attention neural networks for text classification

    Guangxi LIXuanqiang ZHAOXin WANG
    297-309页
    查看更多>>摘要：An emerging direction of quantum computing is to establish meaningful quantum applications in various fields of artificial intelligence,including natural language processing(NLP).Although some efforts based on syntactic analysis have opened the door to research in quantum NLP(QNLP),limitations such as heavy syntactic preprocessing and syntax-dependent network architecture make them impracticable on larger and real-world data sets.In this paper,we propose a new simple network architecture,called the quantum self-attention neural network(QSANN),which can compensate for these limitations.Specifically,we introduce the self-attention mechanism into quantum neural networks and then utilize a Gaussian projected quantum self-attention serving as a sensible quantum version of self-attention.As a result,QSANN is effective and scalable on larger data sets and has the desirable property of being implementable on near-term quantum devices.In particular,our QSANN outperforms the best existing QNLP model based on syntactic analysis as well as a simple classical self-attention neural network in numerical experiments of text classification tasks on public data sets.We further show that our method exhibits robustness to low-level quantum noises and showcases resilience to quantum neural network architectures.
      原文链接:
    • 万方数据
    • 维普

    Continuous variable quantum teleportation and remote state preparation between two space-separated local networks

    Siyu RENDongmei HANMeihong WANGXiaolong SU...
    310-318页
    查看更多>>摘要：Implementing quantum communication between space-separated local networks is essential for designing global quantum networks.In this study,we propose quantum teleportation and remote state preparation schemes between users of two space-separated local networks established by continuous-variable multipartite entangled states.In the proposed schemes,the quantum nodes belonging to the two distant local networks are first entangled by entanglement swapping,and then quantum communication protocols are realized.We show that quantum teleportation between any two users belonging to space-separated local networks can be realized with the assistance of other users,and squeezed thermal states can be remotely prepared in one local network by performing a homodyne projective measurement on the state in another distant local network.Our results provide a feasible approach for quantum communication between space-separated quantum networks with multipartite entangled states.
      原文链接:
    • 万方数据
    • 维普

    Quantum key distribution over a mimicked dynamic-scattering channel

    Qi-Hang LUFang-Xiang WANGWei CHENHai-Yang FU...
    319-326页
    查看更多>>摘要：Free-space quantum key distribution(QKD)plays an important role in the global quantum network.However,free space channels suffer from the atmospheric turbulence and scattering effects of haze,fog,and dust,which significantly weaken the performance of QKD or even block the secure quantum link.Here,we prove the performance of QKD over a dynamic scattering channel can be enhanced significantly using a fast wavefront shaping technique.The system achieves on average 10-dB enhancement of quantum transmission efficiency and establishes a secure quantum link for QKD.Our work demonstrates the feasibility of QKD through free-space dynamic scattering channels and enhances the deployment capability of complex-channel QKD system.
      原文链接:
    • 万方数据
    • 维普