检索结果-南通市图书馆

Threshold Selection and Resource Allocation for Quantized Identification

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2024年第1期37卷 204-229页

作者： WANG Ying LI Xin zhao yanlong ZHANG Ji-Feng Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China

This paper is concerned with the optimal threshold selection and resource allocation problems of quantized identification, whose aims are improving identification efficiency under limited resources. Firstly, the first-order asymptotically optimal quantized identification theory is extended to the weak persistent excitation condition. Secondly, the characteristics of time and space complexities are established based on the Cramér-Rao lower bound of quantized systems. On these basis, the optimal selection methods of fixed thresholds and adaptive thresholds are established under aperiodic signals, which answer how to achieve the best efficiency of quantized identification under the same time and space complexity. In addition, based on the principle of maximizing the identification efficiency under a given resource, the optimal resource allocation methods of quantized identification are given for the cases of fixed thresholds and adaptive thresholds, respectively, which show how to balance time and space complexity to realize the best identification efficiency of quantized identification.

关键词： Quantized output resource allocation system identification threshold selection.

在线全文

学校读者我要写书评

暂无评论

MOF基材料吸附去除食品污染物研究进展

北京工业大学学报 2024年第6期50卷 763-776页

作者：赵砚珑黄光灿陈强北京工业大学环境与生命学部北京100124

食品安全不仅直接关系到人民群众的生命健康,而且还是社会和谐稳定的重要基础。食品在生产、加工、储存等过程中均可能产生或引入各种类型的污染物,例如重金属、有机农药、染料、真菌毒素和持久性有机污染物等。去除被污染食品中的污染... 详细信息

食品安全不仅直接关系到人民群众的生命健康,而且还是社会和谐稳定的重要基础。食品在生产、加工、储存等过程中均可能产生或引入各种类型的污染物,例如重金属、有机农药、染料、真菌毒素和持久性有机污染物等。去除被污染食品中的污染物是保证食品安全和人类健康的重要举措,目前主要的处理手段包括催化降解、化学氧化、萃取、酶降解、微生物降解及吸附去除等方法。其中吸附法较其他方法来说具有工艺简便、能耗低、操作灵活等优势,是处理食品污染物最具前景的方式之一。金属有机框架(metal-organic frameworks,MOFs)是一类新兴的多孔材料,比表面积大、孔隙率高、孔道可修饰等特点使其在吸附去除食品污染物方面具有广阔的研究与应用前景。介绍了近年来MOF基吸附剂吸附去除各类食品污染物的主要研究进展;从静电作用、酸碱/配位作用、π-π堆积作用、氢键作用以及协同作用等方面系统总结了MOF基吸附剂对食品污染物的各类吸附机理;对该类研究所面临的挑战及未来发展趋势进行了总结与展望,旨在为食品安全领域MOF基吸附剂的研究提供实例借鉴与理论指导。

关键词：金属有机框架(MOFs) 吸附吸附剂吸附机理食品安全食品污染物

基于转移概率分布的组合信用转移风险参数估计与压力测试

在线全文

学校读者我要写书评

暂无评论

系统工程理论与实践 2024年第3期44卷 893-911页

作者：史若诗何寅杰赵延龙包莹中国工商银行博士后科研工作站北京100140 中国科学院数学与系统科学研究院系统控制重点实验室北京100190 中国科学院大学数学科学学院北京100049 中国工商银行总行风险管理部北京100140

近年来,压力测试因其衡量金融危机等极端环境下风险的特性在现代银行风险管理中发挥着越来越重要的作用.准确衡量组合风险受系统性因素的驱动作用,是有效控制金融风险,防范金融危机的关键.本文研究了组合信用风险参数估计与压力测试问题... 详细信息

近年来,压力测试因其衡量金融危机等极端环境下风险的特性在现代银行风险管理中发挥着越来越重要的作用.准确衡量组合风险受系统性因素的驱动作用,是有效控制金融风险,防范金融危机的关键.本文研究了组合信用风险参数估计与压力测试问题,建立了包含系统性因子和多级相关性系数的Vasicek信用转移模型,分析了相关性系数对各评级间信用转移概率的影响,给出了使得评级单调一致的相关性系数条件,保证了信用评级转移概率的单调一致性;构造了基于降级概率分布的参数估计方法,利用转移概率矩阵推导出市场均衡状态下的评级寿命分布,进而给出了相关性系数和系统性因子的估计算法.与已有算法相比,本文提出的方法减弱了系统性因子固定偏差的影响,克服了算法对系统性因子分布的依赖,在降低计算代价的同时提高了估计的精确度.仿真实验结果表明,本文提出的方法有效提高了计算速度,对系统性因子、相关系数及组合损失的估计效果都显著优于已有方法;利用该方法估计的极端损失可以更充分地覆盖样本外组合损失,使得在压力测试中能够更好地预判和防范金融风险,维护金融市场稳定.

关键词：组合信用风险 Vasicek模型信用转移概率矩阵压力测试

Consensus of switched multi-agent systems with binary-valued communications

在线全文

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2022年第6期65卷 189-202页

作者： Min HU Ting WANG yanlong zhao The Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

This paper studies the consensus of switched multi-agent systems(MAS) with binary-valued communications. Different from the existing studies on switched MAS considering precise observations,each agent studied in this research only receives binary-valued information with stochastic noises from its neighbors’ states. Further, unlike the existing studies on MAS with binary-valued information in a fixed topology, in this paper, we consider the jointly connected undirected graphs, each of which switches with non-zero probability. The consensus algorithm comprises of two stages: first, the connected agents employ a recursive projection algorithm to estimate their neighbors’ states based on the binary-valued communications;second, the control law of the connected agents is developed based on the estimations to upgrade their *** is proved that both the speed of the estimation convergence to the real states and the consensus speed of the states can achieve O(1/t) when the iteration step is given a proper value. Furthermore, the results indicate that the larger the value of the lowest probability that a graph emerges with, the more easily the consensus could be achieved. Finally, a simulation is presented to demonstrate the theoretical analysis.

关键词： binary-valued system switched multi-agent system recursive projection algorithm consensus jointly connected undirected topologies

Identification of the gain system with quantized observations and bounded persistent excitations

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2014年第1期57卷 217-231页

作者： GUO Jin zhao yanlong Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems ScienceChinese Academy of Sciences

System identification with quantized observations and persistent excitations is a fundamental and difcult *** the first step,this paper takes the gain system for example to investigate the identification with quantized observations and bounded persistently exciting ***,the identification with single threshold quantization is considered.A projection recursive algorithm is proposed to estimate the unknown *** use of the conditional expectation of quantized observations with respect to the estimates,the algorithm is shown to be both mean-square and almost surely *** upper bound of the convergence rate is also obtained,which has the same order as the one of the optimal estimation in the case where the system output is exactly ***,for the multi-threshold quantization,the identification algorithm is similarly constructed and its asymptotic property is *** a multi-linear transformation,the optimal scheme of quantization values and thresholds is given.A numerical example is simulated to demonstrate the efectiveness of the algorithms and the main results obtained.

关键词： system identification quantized observation bounded persistent excitation binary-valued output multi-threshold quantization convergence convergence rate

Iterative parameter estimate with batched binary-valued observations

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2016年第5期59卷 158-175页

作者： yanlong zhao Wenjian BI Ting WANG Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences

In this paper, we consider linear system identification with batched binary-valued *** constructed an iterative parameter estimate algorithm to achieve the maximum likelihood(ML) *** first interesting result was that there exists at most one finite ML solution for this specific maximum likelihood problem, which was induced by the fact that the Hessian matrix of the log-likelihood function was negative definite under binary data and Gaussian system noises. The global concave property and local strongly concave property of the log-likelihood function were obtained. Under mild conditions on the system input, we proved that the ML function has a unique maximum point. The second main result was that the ML estimate was consistent under persistent excitation inputs, which infers the effectiveness of ML estimate. Finally, the proposed iterative estimate algorithm converged to a fixed vector with an exponential rate that was proved by constructing a Lyapunov function. A more interesting result was that the limit of the iterative algorithm achieved the maximization of the ML function. Numerical simulations are illustrated to support the theoretical results obtained in this paper well.

关键词： Binary-valued observation maximum likelihood estimate strongly convex system identification exponential rate

FIR system identification with set-valued and precise observations from multiple sensors

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2019年第5期62卷 179-194页

作者： Hang ZHANG Ting WANG yanlong zhao Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences

This paper considers the system identification problem for FIR(finite impulse response) systems with set-valued and precise observations received from multiple sensors. A fusion estimation algorithm based on some suitable identification algorithms for different types of observations is proposed. In particular, least square method is chosen for FIR systems with precise observations, while empirical measure method and EM algorithm are chosen for FIR systems with set-valued observations in the cases of periodic and general system inputs, respectively. Then, the quasi-convex combination estimator(QCCE) fusing the two different estimators by a linear combination with appropriate weights is constructed. Furthermore, the convergence properties are theoretically analyzed in terms of strong consistency and asymptotic efficiency. The fused estimator QCCE is proved to achieve the Cram′er-Rao(CR) lower bound asymptotically under periodic inputs. Extensive numerical simulations validate the superiority of the fusion estimation algorithm under both periodic and general inputs.

关键词： system identification FIR system set-valued precise fusion estimation quasi-convex combination estimator

Distributed Recursive Projection Identification with Binary-Valued Observations

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Science & Complexity 2021年第5期34卷 2048-2068页

作者： WANG Ying zhao yanlong ZHANG Ji-Feng Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China.

This paper investigates a distributed recursive projection identification problem with binaryvalued observations built on a sensor network,where each sensor in the sensor network measures partial information of the unknown parameter only,but each sensor is allowed to communicate with its neighbors.A distributed recursive projection algorithm is proposed based on a specific projection operator and a diffusion *** authors establish the upper bound of the accumulated regrets of the adaptive predictor without any requirement of excitation ***,the convergence of the algorithm is given under the bounded cooperative excitation condition,which is more general than the previously imposed independence or persistent excitations on the system regressors and maybe the weakest one under binary observations.A numerical example is supplied to demonstrate the theoretical results and the cooperative effect of the sensors,which shows that the whole network can still fulfill the estimation task through exchanging information between sensors even if any individual sensor cannot.

关键词： Adaptive predictor binary-valued observations cooperative excitations distributed parameter estimation

Consensus Control With a Constant Gain for Discrete-time Binary-valued Multi-agent Systems Based on a Projected Empirical Measure Method

在线全文

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2019年第4期6卷 1052-1059页

作者： Ting Wang Min Hu yanlong zhao IEEE the Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China the School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100149China

This paper studies the consensus control of multiagent systems with binary-valued *** algorithm alternating estimation and control is *** agent estimates the states of its neighbors based on a projected empirical measure method for a holding *** on the estimates,each agent designs the consensus control with a constant gain at some skipping *** states of the system are updated by the designed control,and the estimation and control design will be *** the estimation,the projected empirical measure method is proposed for the binary-valued *** algorithm can ensure the uniform boundedness of the estimates and the mean square error of the estimation is proved to be at the order of the reciprocal of the holding time(the same order as that in the case of accurate outputs).For the consensus control,a constant gain is designed instead of the stochastic approximation based gain in the existing literature for binary-valued ***,there is no need to make modification for control since the uniform boundedness of the estimates ensures the uniform boundedness of the agents’***,the systems updated by the designed control are proved to achieve consensus and the consensus speed is faster than that in the existing *** are given to demonstrate the theoretical results.

关键词： Binary-valued observations consensus control constant gain convergence rate multi-agent systems projected empirical measure method