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On convergence of covariance matrix of empirical Bayes hyper-parameter estimator

Control Theory and Technology 2024年第2期22卷 149-162页

作者： Yue Ju Biqiang Mu tianshi chen School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong KongShenzhenShenzhen518172GuangdongChina Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology10044StockholmSweden Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of SciencesBeijing100190China

Regularized system identification has become the research frontier of system identification in the past *** related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to *** this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been ***,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is *** general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance ***,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter *** this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting ***,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.

关键词： Regularized system identification Hyper-parameter estimator Empirical Bayes Convergence of covariance matrix

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Global robust stabilization of feedforward systems with uncertainties

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控制理论与应用（英文版） 2010年第3期8卷 262-270页

作者： tianshi chen Jie HUANG Department of Electrical Engineering Link6ping University Link6ping Sweden Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China

This paper studies the global robust stabilization problem for a class of feedforward systems that is subject to both dynamic and time-varying static uncertainties. A small gain theorem-based bottom-up recursive design is developed for constructing a nested saturation control law. At each recursion, two versions of small gain theorem with restrictions are employed to establish the global attractiveness and local stability of the closed-loop system at the equilibrium point, respectively.

关键词： Robust control Nonlinear systems Asymptotic stabilization

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A survey of neural network accelerators

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Frontiers of Computer Science 2017年第5期11卷 746-761页

作者： Zhen LI Yuqing WANG Tian ZHI tianshi chen State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer Science and Technology University of Science and Technology of China Hefei 230026 China

Machine-learning techniques have recently been proved to be successful in various domains, especially in emerging commercial applications. As a set of machine- learning techniques, artificial neural networks （ANNs）, requiring considerable amount of computation and memory, are one of the most popular algorithms and have been applied in a broad range of applications such as speech recognition, face identification, natural language processing, ect. Conventionally, as a straightforward way, conventional CPUs and GPUs are energy-inefficient due to their excessive effort for flexibility. According to the aforementioned situation, in recent years, many researchers have proposed a number of neural network accelerators to achieve high performance and low power consumption. Thus, the main purpose of this literature is to briefly review recent related works, as well as the DianNao-family accelerators. In summary, this review can serve as a reference for hardware researchers in the area of neural networks.

关键词： neural networks accelerators FPGAs ASICs,DianNao series

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Stealth-ACK: stealth transmissions of No C acknowledgements

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Science China(Information Sciences) 2017年第9期60卷 21-35页

作者： Jinhua TAO Shi QIU Shaoli LIU tianshi chen Rui MAO Institute of Computing Technology Chinese Academy of Sciences College of Computer Science and Software Engineering Shenzhen University

Network-on-Chip(No C) is a promising replacement of bus architecture due to its better *** state-of-the-art No Cs, each packet contains several fixed-length flits, which facilitates allocations of network resources but brings in many unused bits. In this paper, we propose a novel technique called Stealth-ACK to effectively address the above problem. Stealth-ACK leverages unused bits in head flits of non-ACK packets to carry and stealthily transmit ACK information. Such stealth transmissions of ACK information effectively reduce not only the amount of dedicated ACK packets on No C, but also the number of unused bits in head flits of non-ACK packets, which significantly reduces wastes on No C bandwidth. Experimental results show that Stealth-ACK averagely increases the throughput of 16 × 16 2-D mesh No C by 11.9%, and averagely reduces the No C latency by 34.8% on application traces of SPLASH-2. Moreover, Stealth-ACK only requires trivial hardware modification to basic router architectures, which incurs negligible power consumption and area cost.

关键词： networks-on-chip acknowledgement packet router architecture optimisation routing algorithm

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Special issue on system identiﬁcation and estimation

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Control Theory and Technology 2024年第2期22卷 147-148页

作者： Weixing Zheng tianshi chen chengpu Yu Wenxiao Zhao Western Sydney University SydneyAustralia The Chinese University of Hong Kong ShenzhenChina Beijing Institute of Technology BeijingChina The Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijingChina

It is our great pleasure and honor to organize this special issue“System Identiﬁcation and Estimation”.System identiﬁcation has been a surprisingly lively and resilient area of research in the control community for many *** grew out of statisticians’interest in time series analysis beginning in the 1940s and became a“regular control topic”in the 1960s,as indicated by theﬁrst IFAC Symposium on System Identiﬁcation held in Prague,Czech Republic,in *** years later,it is still an important area of research in theﬁeld of *** is relevant to ask why the interest in system identiﬁcation has remained so *** answer might be that more and more applications in engineering require mathematical models and the combined use of system identiﬁcation and physical modeling is the basic way to obtain reliable *** special issue is focusing on the latest development,trends,and novel methods for system identiﬁcation and estimation and these contributions will give interesting and inspiring insights into the current status of the area.

关键词： estimation system IFAC

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MW-DLA:a dynamic bit width deep learning accelerator

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High Technology Letters 2020年第2期26卷 145-151页

作者： Li Zhen Zhi Tian Liu Enhe Liu Shaoli chen tianshi Intelligent Processor Research Center Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190P.R.China University of Chinese Academy of Sciences Beijing 100049P.R.China Cambricon Technologies Corporation Limited Beijing 100191P.R.China

Deep learning algorithms are the basis of many artificial intelligence *** algorithms are both computationally intensive and memory intensive,making them difficult to deploy on embedded *** various deep learning accelerators(DLAs)are proposed and applied to achieve better performance and lower power ***,most deep learning accelerators are unable to support multiple data *** research proposes the MW-DLA,a deep learning accelerator supporting dynamic configurable *** work analyzes the data distribution of different data types in different layers and trains a typical network with per-layer *** a result,the proposed MW-DLA achieves 2X performance and more than 50%memory requirement for AlexNet with less than 5.77%area overhead.

关键词： deep learning accelerator(DLA) per-layer representation multiple-precision arithmetic unit

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Pros and Cons: Autophagy in Acute Spinal Cord Injury

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Neuroscience Bulletin 2019年第5期35卷 941-945页

作者： Zheng Li tianshi chen Yuanwu Cao Xiaoxing Jiang Haodong Lin Jian Zhang Zixian chen Department of Orthopedics Zhongshan Hospital Fudan University Shanghai 200032 China Department of Orthopedics People’s Hospital of Boluo County Huizhou 516100 China Department of Orthopedic Surgery Shanghai General Hospital Shanghai Jiaotong University School of Medicine Shanghai 200080 China

Autophagy plays an important role in the development and pathogenesis of various diseases. It can be induced by a variety of events such as hypoxia, nutrient-starvation, and mechanical damage. Many neurological disorders such Parkinson’s disease, Alzheimer’s disease, amyotrophic lateral sclerosis, Huntington’s disease, cerebral ischemia, and acute spinal cord injury (ASCI), are closely related to autophagy. However, therapeutic strategies to manipulate autophagy have not yet been fully deciphered due to the limited knowledge of the molecular mechanisms underlying autophagy in these disorders.

关键词： Pros Cons: Autophagy Acute Spinal Cord Injury

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基于模型树的多核设计空间探索技术

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计算机辅助设计与图形学学报 2012年第6期24卷 710-720页

作者：郭崎陈天石陈云霁中国科学院计算技术研究所计算机体系结构国家重点实验室北京100190 中国科学院研究生院北京100049 北京龙芯中科技术服务中心有限公司北京100190

处理器设计面临的重要挑战是如何在庞大的设计空间中高效地找到满足约束的设计结构,而预测模型方法是探索复杂设计空间的重要方法.为了提高预测模型的实用性,提出一种基于模型树的多核设计空间探索技术.首先对整个设计空间中部分设计结... 详细信息

处理器设计面临的重要挑战是如何在庞大的设计空间中高效地找到满足约束的设计结构,而预测模型方法是探索复杂设计空间的重要方法.为了提高预测模型的实用性,提出一种基于模型树的多核设计空间探索技术.首先对整个设计空间中部分设计结构进行采样模拟,然后通过模型树算法构建设计参数与处理器响应之间的预测模型,最后通过该模型预测出其他设计结构的响应以找到满足约束的最优设计.实验结果表明,与现有的基于支持向量机和人工神经网络的预测模型技术相比,针对性能预测,采用文中技术能够提高74.87%和38.87%的准确度;针对能耗预测,能够提高2.66%和16.82%的准确度.

关键词：设计空间探索多核处理器预测模型模型树

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超大规模集成电路可调试性设计综述

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计算机研究与发展 2012年第1期49卷 21-34页

作者：钱诚沈海华陈天石陈云霁中国科学院计算机系统结构重点实验室北京100190 中国科学院计算技术研究所微处理器技术研究中心北京100190 中国科学院研究生院北京100049

随着硬件复杂度的不断提高和并行软件调试的需求不断增长,可调试性设计已经成为集成电路设计中的重要内容.一方面,仅靠传统的硅前验证已经无法保证现代超大规模复杂集成电路设计验证的质量,因此作为硅后验证重要支撑技术的可调试性设计... 详细信息

随着硬件复杂度的不断提高和并行软件调试的需求不断增长,可调试性设计已经成为集成电路设计中的重要内容.一方面,仅靠传统的硅前验证已经无法保证现代超大规模复杂集成电路设计验证的质量,因此作为硅后验证重要支撑技术的可调试性设计日渐成为大规模集成电路设计领域的研究热点.另一方面,并行程序的调试非常困难,很多细微的bug无法直接用传统的单步、断点等方法进行调试,如果没有专门的硬件支持,需要耗费极大的人力和物力.全面分析了现有的可调试性设计,在此基础上归纳总结了可调试性设计技术的主要研究方向并介绍了各个方向的研究进展,深入探讨了可调试性结构设计研究中的热点问题及其产生根源,给出了可调试性结构设计领域的发展趋势.

关键词：调试验证硅后验证并行程序调试可调试性设计

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片上多核处理器共享资源分配与调度策略研究综述

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计算机研究与发展 2013年第10期50卷 2212-2227页

作者：王磊刘道福陈云霁陈天石李玲中国科学院计算机系统结构重点实验室北京100190 中国科学院大学北京100049 龙芯中科技术有限公司北京100190

对于片上多核处理器,如何在多线程间公平有效地分配调度有限的共享资源是一个很重要的问题.随着处理器核规模的增长,多线程对于系统中有限的共享资源的争夺将愈发激烈,由此导致的对于系统性能的影响也将更加显著.为了缓解乃至解决这一问... 详细信息

对于片上多核处理器,如何在多线程间公平有效地分配调度有限的共享资源是一个很重要的问题.随着处理器核规模的增长,多线程对于系统中有限的共享资源的争夺将愈发激烈,由此导致的对于系统性能的影响也将更加显著.为了缓解乃至解决这一问题,除了增加可用共享资源外,一个能够公平有效地在多线程间分配共享资源的调度算法也至关重要.在各类共享资源中,对于系统性能有着最大影响的是共享缓存和动态随机存储器(dynamic random-access memory,DRAM)系统.对于共享缓存,可以通过缓存分区来降低由于线程间的争夺所带来的影响;对于DRAM系统,可以采取适当的调度算法来调节各个线程发出的访存请求的服务优先级,从而改善系统性能.首先分别以系统吞吐量和公平性为优化目标介绍了一系列对共享缓存的分区调度算法,并针对缓存分区粒度过大的问题给出了相关解决方案.然后从利用线程的访存行为特征和借鉴网络路由算法等多个角度介绍了DRAM的调度算法.研究了从全局出发的联合调度算法,以解决针对不同共享资源的调度算法间相互矛盾的问题.最后从不同角度对于今后的研究进行了展望.

关键词：片上多核处理器多线程共享缓存缓存分区访存调度

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