基于1991~2020年发表在Web of Science(WOS)核心数据库的双元创新学术论文,对双元创新研究进行了可视化计量分析和系统性内容梳理:①从文献产出趋势、合作网络、发表平台和关键节点文献等方面呈现双元创新研究概况;②总结双元创新的基...基于1991~2020年发表在Web of Science(WOS)核心数据库的双元创新学术论文,对双元创新研究进行了可视化计量分析和系统性内容梳理:①从文献产出趋势、合作网络、发表平台和关键节点文献等方面呈现双元创新研究概况;②总结双元创新的基本思想与逻辑,提炼分析双元创新的4种基本关系,构建基于“影响机制-作用过程-作用效果”的双元创新整合研究框架;③在对比中英文代表性文献的基础上,提出应基于跨学科、多层次与多因素交互、多研究方法、智能化和数字化驱动等视角开展中国情境下双元创新研究的建议。展开更多
This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time systems.Firstly,the authors propose an online algorithm with critic and ...This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time systems.Firstly,the authors propose an online algorithm with critic and actor NNs to solve the optimal control problem and provide an event-triggered method to reduce communication and computation burdens.Moreover,the authors design weight estimation for critic and actor NNs based on gradient descent method and achieve uniformly ultimate boundednesss(UUB)estimation results.Furthermore,by using bounded NN weight estimation and dead-zone operator,the authors propose a triggering condition,prove the asymptotic stability of closed-loop system from Lyapunov stability perspective,and exclude the Zeno behavior.Finally,the authors provide a numerical example to illustrate the effectiveness of the proposed method.展开更多
This paper proposes a novel distributed optimization algorithm with fractional order dynamics to solve linear algebraic equations.Firstly,the authors proposed“Consensus+Projection”flow with fractional order dynamics...This paper proposes a novel distributed optimization algorithm with fractional order dynamics to solve linear algebraic equations.Firstly,the authors proposed“Consensus+Projection”flow with fractional order dynamics,which has more design freedom and the potential to obtain a better convergent performance than that of conventional first order algorithms.Moreover,the authors prove that the proposed algorithm is convergent under certain iteration order and step-size.Furthermore,the authors develop iteration order switching scheme with initial condition design to improve the convergence performance of the proposed algorithm.Finally,the authors illustrate the effectiveness of the proposed method with several numerical examples.展开更多
文摘基于1991~2020年发表在Web of Science(WOS)核心数据库的双元创新学术论文,对双元创新研究进行了可视化计量分析和系统性内容梳理:①从文献产出趋势、合作网络、发表平台和关键节点文献等方面呈现双元创新研究概况;②总结双元创新的基本思想与逻辑,提炼分析双元创新的4种基本关系,构建基于“影响机制-作用过程-作用效果”的双元创新整合研究框架;③在对比中英文代表性文献的基础上,提出应基于跨学科、多层次与多因素交互、多研究方法、智能化和数字化驱动等视角开展中国情境下双元创新研究的建议。
基金supported by the National Natural Science Foundation of China under Grant Nos.61973002,62103003the Anhui Provincial Natural Science Foundation under Grant No.2008085J32+2 种基金the National Postdoctoral Program for Innovative Talents under Grant No.BX20180346the General Financial Grant from the China Postdoctoral Science Foundation under Grant No.2019M660834the Excellent Young Talents Program in Universities of Anhui Province under Grant No.gxyq2019002.
文摘This paper develops a novel event-triggered optimal control approach based on state observer and neural network(NN)for nonlinear continuous-time systems.Firstly,the authors propose an online algorithm with critic and actor NNs to solve the optimal control problem and provide an event-triggered method to reduce communication and computation burdens.Moreover,the authors design weight estimation for critic and actor NNs based on gradient descent method and achieve uniformly ultimate boundednesss(UUB)estimation results.Furthermore,by using bounded NN weight estimation and dead-zone operator,the authors propose a triggering condition,prove the asymptotic stability of closed-loop system from Lyapunov stability perspective,and exclude the Zeno behavior.Finally,the authors provide a numerical example to illustrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China under Grant Nos.62103003,62073001,and 61973002the Anhui Provincial Key Research and Development Project under Grant2022i01020013+3 种基金the University Synergy Innovation Program of Anhui Province under Grant No.GXXT-2021-010the Anhui Provincial Natural Science Foundation under Grant No.2008085J32the National Postdoctoral Program for Innovative Talents under Grant No.BX20180346the General Financial Grant from the China Postdoctoral Science Foundation under Grant No.2019M660834。
文摘This paper proposes a novel distributed optimization algorithm with fractional order dynamics to solve linear algebraic equations.Firstly,the authors proposed“Consensus+Projection”flow with fractional order dynamics,which has more design freedom and the potential to obtain a better convergent performance than that of conventional first order algorithms.Moreover,the authors prove that the proposed algorithm is convergent under certain iteration order and step-size.Furthermore,the authors develop iteration order switching scheme with initial condition design to improve the convergence performance of the proposed algorithm.Finally,the authors illustrate the effectiveness of the proposed method with several numerical examples.
