中国科学院数学与系统科学研究院期刊网

25 August 2024, Volume 37 Issue 4
    

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  • YANG Xu, ZENG Shaofeng, LIU Zhiyong
    Journal of Systems Science & Complexity. 2024, 37(4): 1351-1367. https://doi.org/10.1007/s11424-024-3141-0
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    Feature correspondence is a crucial aspect of various computer vision and robot vision tasks. Unlike traditional optimization-based matching techniques, researchers have recently adopted a learning-based approach for matching, but these methods face challenges in dealing with outlier features. This paper presents an outlier robust feature correspondence method that employs a pruned attentional graph neural network and a matching layer to address the outlier issue. Additionally, the authors introduce a modified cross-entropy matching loss to handle the outlier problem. As a result, the proposed method significantly enhances the performance of learning-based matching algorithms in the presence of outlier features. Benchmark experiments confirm the effectiveness of the proposed approach.
  • PENG Qingqing, ZHANG Zhifei
    Journal of Systems Science & Complexity. 2024, 37(4): 1368-1391. https://doi.org/10.1007/s11424-024-3132-1
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    In this paper, the authors consider the stabilization and blow up of the wave equation with infinite memory, logarithmic nonlinearity and acoustic boundary conditions. The authors discuss the existence of global solutions for the initial energy less than the depth of the potential well and investigate the energy decay estimates by introducing a Lyapunov function. Moreover, the authors establish the finite time blow up results of solutions and give the blow up time with upper bounded initial energy.
  • FENG Siqi, GAO Lei, WANG Guangchen, XIAO Hua
    Journal of Systems Science & Complexity. 2024, 37(4): 1392-1412. https://doi.org/10.1007/s11424-024-3163-7
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    Motivated by a duopoly game problem, the authors study an optimal control problem where the system is driven by Brownian motion and Poisson point process and has elephant memory for the control variable and the state variable. Firstly, the authors establish the unique solvability of an anticipated backward stochastic differential equation, derive a stochastic maximum principle, and prove a verification theorem for the aforementioned optimal control problem. Furthermore, the authors generalize these results to nonzero-sum stochastic differential game problems. Finally, the authors apply the theoretical results to the duopoly game problem and obtain the corresponding Nash equilibrium solution.
  • HONG Xin, DONG Yi
    Journal of Systems Science & Complexity. 2024, 37(4): 1413-1424. https://doi.org/10.1007/s11424-024-3173-5
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    With the development of intelligent technology, the problem of LiDAR-based localization has played an increasingly important role in the localization of robots in unmanned systems. Since the dense point clouds from the environment requires a large amount of memory, specific and stable structural features, such as pole-like objects in the environment, can serve as the ideal landmarks for localization in unmanned systems, which can effectively reduce the memory usage and mitigate the effects of dynamic environment changes. In this paper, the authors propose a pole-like objects extraction approach and then, it is applied into the localization system of mobile robots. Under the same experimental conditions, the proposed method can extract more pole-like objects and achieve better long-term localization accuracy than some existing methods in different urban environmental datasets.
  • GAO Wenhui, LIN Yaning, ZHANG Weihai
    Journal of Systems Science & Complexity. 2024, 37(4): 1425-1445. https://doi.org/10.1007/s11424-024-2480-1
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    This paper designs an incentive Stackelberg strategy for the discrete-time stochastic systems with mean-field terms. Sufficient conditions for the existence of such a design are suggested. Moreover, the incentive strategy is obtained as a feedback form including the deviation of the state and its mathematical expectation. Also, the stability analysis is involved. It is found that the stability can be guaranteed by the follower. In addition, the specific algorithm is proposed and its effectiveness is checked by two examples.
  • QIAO Nan, LI Tao
    Journal of Systems Science & Complexity. 2024, 37(4): 1446-1469. https://doi.org/10.1007/s11424-024-2421-z
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    The authors propose a data-driven direct adaptive control law based on the adaptive dynamic programming (ADP) algorithm for continuous-time stochastic linear systems with partially unknown system dynamics and infinite horizon quadratic risk-sensitive indices. The authors use online data of the system to iteratively solve the generalized algebraic Riccati equation (GARE) and to learn the optimal control law directly. For the case with measurable system noises, the authors show that the adaptive control law approximates the optimal control law as time goes on. For the case with unmeasurable system noises, the authors use the least-square solution calculated only from the measurable data instead of the real solution of the regression equation to iteratively solve the GARE. The authors also study the influences of the intensity of the system noises, the intensity of the exploration noises, the initial iterative matrix, and the sampling period on the convergence of the ADP algorithm. Finally, the authors present two numerical simulation examples to demonstrate the effectiveness of the proposed algorithms.
  • HU Haokun, MO Lipo, CAO Xianbing
    Journal of Systems Science & Complexity. 2024, 37(4): 1470-1487. https://doi.org/10.1007/s11424-024-2149-9
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    This paper studies the optimization problem of heterogeneous networks under a time-varying topology. Each agent only accesses to one local objective function, which is nonsmooth. An improved algorithm with noisy measurement of local objective functions' sub-gradients and additive noises among information exchanging between each pair of agents is designed to minimize the sum of objective functions of all agents. To weaken the effect of these noises, two step sizes are introduced in the control protocol. By graph theory, stochastic analysis and martingale convergence theory, it is proved that if the sub-gradients are uniformly bounded, the sequence of digraphs is balanced and the union graph of all digraphs is joint strongly connected, then the designed control protocol can force all agents to find the global optimal point almost surely. At last, the authors give some numerical examples to verify the effectiveness of the stochastic sub-gradient algorithms.
  • XIE Siyu, ZHANG Shujun, WANG Ziming, GAN Die
    Journal of Systems Science & Complexity. 2024, 37(4): 1488-1506. https://doi.org/10.1007/s11424-024-3297-7
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    In this paper, the authors consider a sparse parameter estimation problem in continuous-time linear stochastic regression models using sampling data. Based on the compressed sensing (CS) method, the authors propose a compressed least squares (LS) algorithm to deal with the challenges of parameter sparsity. At each sampling time instant, the proposed compressed LS algorithm first compresses the original high-dimensional regressor using a sensing matrix and obtains a low-dimensional LS estimate for the compressed unknown parameter. Then, the original high-dimensional sparse unknown parameter is recovered by a reconstruction method. By introducing a compressed excitation assumption and employing stochastic Lyapunov function and martingale estimate methods, the authors establish the performance analysis of the compressed LS algorithm under the condition on the sampling time interval without using independence or stationarity conditions on the system signals. At last, a simulation example is provided to verify the theoretical results by comparing the standard and the compressed LS algorithms for estimating a high-dimensional sparse unknown parameter.
  • ZHANG Zhibing, ZHOU Dapeng, WANG Yeguang, GAO Wanxin, ZHANG Yanjun
    Journal of Systems Science & Complexity. 2024, 37(4): 1507-1525. https://doi.org/10.1007/s11424-024-3364-0
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    The stability margin is a vital indicator for assessing the safety level of aircraft control systems. It should maintain sufficient stability margin to ensure safety during flight, especially in the process of large maneuver operations. The stability margin is generally quantified by the Bode diagram, which strictly depends on the system parameters and the open-loop transfer function. However, due to the uncertain flight environments, transmission delays of sensors and mode switchings, etc., there exist large parameter and structure uncertainties in the aircraft control systems, which make it difficult to precisely configure the stability margin to the desired value by the usual control methods. To address this problem, an indirect adaptive control strategy is proposed in this paper, where an adaptive PI control law with the capability of self-configuration of stability margin is developed. The developed control law not only achieves stable time-varying command tracking in the time domain, but also is able to automatically configure the phase margin and gain margin in the frequency domain. Finally, the simulation of the one-degree-of-freedom roll rate control model of the air vehicle verifies the validity of the proposed control method.
  • SHENG Ning, LIU Yang, CHI Ronghu, AI Zidong
    Journal of Systems Science & Complexity. 2024, 37(4): 1526-1544. https://doi.org/10.1007/s11424-024-3166-4
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    This paper considers the adaptive finite-time control and observer design method for a class of non-strict feedback systems with unmeasurable states, unknown nonlinear dynamics and actuator faults. In this paper, an observer is proposed to estimate the unmeasurable states in finite-time based on adaptive technique and neural networks, while the actuator faults are not included. Command filter is used to solve the computational explosion and singularity problems caused by the traditional backstepping and non-strict feedback structure, respectively. Since the fault efficiency indicators in real systems are not available, two-layer neural networks are adopted, where the first network is to estimate the unknown nonlinearities of systems and the second one is to estimate fault efficiency indicators and unknown nonlinear terms. The proposed scheme guarantees that states are bounded through stability theorem. Finally, two experiments including a numerical example and a spring-mass-damper system are given to verify the effectiveness of the proposed method.
  • FAN Xianrui, LI Yongming, TONG Shaocheng
    Journal of Systems Science & Complexity. 2024, 37(4): 1545-1560. https://doi.org/10.1007/s11424-024-3401-z
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    This paper studies the finite-time fuzzy adaptive output feedback resilient control problem for nonlinear cyber-physical systems (CPSs) with sensor attacks and actuator faults. Fuzzy logic systems (FLSs) are used to approximate the unknown nonlinear functions, and a fuzzy state observer is constructed to estimate the unmeasured states. By combining the Nussbaum function with the backstepping control design technique, a fuzzy adaptive resilient control scheme is designed to successfully address the effects of sensor attacks and actuator faults. It is proved that the controlled system is semi-global practical finite-time stability (SGPFS), and the tracking error converges to a small neighborhood of the origin in a finite time interval. Finally, the simulation and comparison results further demonstrate the effectiveness of the designed control method.
  • YU Miao, FENG Jun-e, XIA Jianwei, FU Shihua, SHEN Hao
    Journal of Systems Science & Complexity. 2024, 37(4): 1561-1580. https://doi.org/10.1007/s11424-024-3167-3
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    In this paper, the approximate synchronization of leader-follower multiagent systems (MAS-s) over finite fields is studied in regard to local and global synchronization. First, the approximately synchronous state set (ASSS) is obtained. Second, combined with ASSS and transient periods, some criteria for the local and global approximate synchronization of systems are given. Moreover, the algorithms for calculating the maximum approximately synchronous basin (MASB) and the maximum control invariant set (MCIS) are presented. Third, the global approximate synchronization of the system is achieved by designing the state feedback control, and a design algorithm of the controller using the truth matrix method is proposed. Moreover, the results of approximate synchronization are degenerated to complete synchronization. Last, two examples are shown to demonstrate the results of this paper.
  • HUANG Bai, SUN Yuying, YANG Boyu
    Journal of Systems Science & Complexity. 2024, 37(4): 1581-1603. https://doi.org/10.1007/s11424-024-2427-6
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    Existing research has shown that political crisis events can directly impact the tourism industry. However, the current methods suffer from potential changes of unobserved variables, which poses challenges for a reliable evaluation of the political crisis impacts. This paper proposes a panel counterfactual approach with Internet search index, which can quantitatively capture the change of crisis impacts across time and disentangle the effect of the event of interest from the rest. It also provides a tool to examine potential channels through which the crisis may affect tourist outflows. This research empirically applies the framework to analyze the THAAD event on tourist flows from the Chinese Mainland to South Korea. Findings highlight the strong and negative short-term impact of the political crisis on the tourists' intentions to visit a place. This paper provides essential evidence to help decision-makers improve the management of the tourism crisis.
  • YOU Kang, WANG Miaomiao, ZOU Guohua
    Journal of Systems Science & Complexity. 2024, 37(4): 1604-1637. https://doi.org/10.1007/s11424-024-2448-1
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    In this paper, the authors propose a frequentist model averaging method for composite quantile regression with diverging number of parameters. Different from the traditional model averaging for quantile regression which considers only a single quantile, the proposed model averaging estimator is based on multiple quantiles. The well-known delete-one cross-validation or jackknife approach is applied to estimate the model weights. The resultant jackknife model averaging estimator is shown to be asymptotically optimal in terms of minimizing the out-of-sample composite final prediction error. Simulation studies are conducted to demonstrate the finite sample performance of the new model averaging estimator. The proposed method is also applied to the analysis of the stock returns data and the wage data.
  • HU Xuemei, PAN Ying, LI Xiang
    Journal of Systems Science & Complexity. 2024, 37(4): 1638-1652. https://doi.org/10.1007/s11424-024-2331-0
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    Accurately predicting stock returns is a conundrum in financial market. Solving this conundrum can bring huge economic benefits for investors and also attract the attention of all circles of people. In this paper the authors combine semi-varying coefficient model with technical analysis and statistical learning, and propose semi-varying coefficient panel data model with individual effects to explore the dynamic relations between the stock returns from five companies: CVX, DFS, EMN, LYB, and MET and five technical indicators: CCI, EMV, MOM, ln ATR, ln RSI as well as closing price (ln CP), combine semi-parametric fixed effects estimator, semi-parametric random effects estimator with the testing procedure to distinguish fixed effects (FE) from random effects (RE), and finally apply the estimated dynamic relations and the testing set to predict stock returns in December 2020 for the five companies. The proposed method can accommodate the varying relationship and the interactive relationship between the different technical indicators, and further enhance the prediction accuracy to stock returns.
  • YANG Yang, ZHAO Letian, CHEN Siyi, YU Dan
    Journal of Systems Science & Complexity. 2024, 37(4): 1653-1671. https://doi.org/10.1007/s11424-024-3086-3
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    In recent years, there has been a growing focus on high-reliability products in industrial and military fields. Storage plays a crucial role in these products, and as a result, research on storage reliability has gained more attention. This paper specifically targets a class of products with complex structures that require long-term storage, regular testing, and maintenance. Firstly, an expression method for system availability is provided based on the reliability structure of the system and the maintenance situation of the constituent equipment in storage. Since the expression of system availability is typically complex and difficult to compute, and the storage life of the system cannot be represented as an explicit function of the reliability indicators of the constituent equipment, it is challenging to evaluate the availability and storage life of repairable systems. To address this, the paper proposes a comprehensive evaluation methodology for assessing the storage reliability of complex repairable systems based on fiducial inference. This approach is employed to derive point estimates and determine the lower fiducial limits for both system availability and storage life. Furthermore, simulation results demonstrate that this comprehensive evaluation method for storage reliability of complex repairable systems is not only convenient but also highly effective.
  • WU Yiting, ZHANG Junyu, HUANG Song
    Journal of Systems Science & Complexity. 2024, 37(4): 1672-1684. https://doi.org/10.1007/s11424-024-3116-1
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    This paper is concerned with nonzero-sum discrete-time stochastic games in Borel state and action spaces under the expected discounted payoff criterion. The payoff function can be unbounded. The transition probability is a convex combination of finite probability measures that are dominated by a probability measure on the state space and depend on the state variable. Under suitable conditions, the authors establish the existence of stationary almost Markov $\varepsilon$-equilibria and give an approximation method via some stochastic games with bounded payoffs. Finally, a production game is introduced to illustrate the applications of the main result, which generalizes the bounded payoff case.
  • SUN Xianwen, ZHANG Lixin
    Journal of Systems Science & Complexity. 2024, 37(4): 1685-1713. https://doi.org/10.1007/s11424-024-3111-6
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    In the past two decades, model averaging, as a way to solve model uncertainty, has attracted more and more attention. In this paper, the authors propose a jackknife model averaging (JMA) method for the quantile single-index coefficient model, which is widely used in statistics. Under model misspecification, the model averaging estimator is proved to be asymptotically optimal in terms of minimizing out-of-sample quantile loss. Simulation experiments are conducted to compare the JMA method with several model selections and model averaging methods, and the results show that the proposed method has a satisfactory performance. The method is also applied to a real dataset.
  • XIA Lili, DU Jiang, ZHANG Zhongzhan
    Journal of Systems Science & Complexity. 2024, 37(4): 1714-1737. https://doi.org/10.1007/s11424-024-3169-1
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    This paper is focused on the goodness-of-fit test of the functional linear composite quantile regression model. A nonparametric test is proposed by using the orthogonality of the residual and its conditional expectation under the null model. The proposed test statistic has an asymptotic standard normal distribution under the null hypothesis, and tends to infinity in probability under the alternative hypothesis, which implies the consistency of the test. Furthermore, it is proved that the test statistic converges to a normal distribution with nonzero mean under a local alternative hypothesis. Extensive simulations are reported, and the results show that the proposed test has proper sizes and is sensitive to the considered model discrepancies. The proposed methods are also applied to two real datasets.
  • LI Xiao, LV Chang, PAN Zhizhong
    Journal of Systems Science & Complexity. 2024, 37(4): 1738-1754. https://doi.org/10.1007/s11424-024-2452-5
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    Elliptic curve cryptography is an important part of nowaday's public key cryptosystem. Counting points of elliptic curves over finite fields is of great significance to the selection of safety curves. At present, there are many $p$-adic algorithms, such as SST algorithm, generalized AGM algorithm, Kedlaya algorithm, etc., which can deal with the situation of finite fields of small characteristics. In this paper, the authors generalize the MSST algorithm of characteristic 2 to general fields of odd characteristic, and propose the generalized MSST algorithm. The generalized MSST algorithm is achieved by combining the advantages of the SST algorithm and the generalized AGM algorithm. If the time complexity of the multiplication of two $n$-bit numbers is denoted as $O(n^{\mu})$, then the time complexity of the generalized MSST algorithm is $O(n^{2\mu+\frac{1}{1+\mu}})$, which is the same as the improved SST algorithm. In practical experiments, the running time of the generalized MSST algorithm is less than that of the improved SST algorithm.
  • CHEN Jingwei, FENG Yong, LIU Yang, WU Wenyuan
    Journal of Systems Science & Complexity. 2024, 37(4): 1755-1771. https://doi.org/10.1007/s11424-024-1313-6
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    Given a $k\times n$ integer primitive matrix $\bm{A}$ (i.e., a matrix can be extended to an $n\times n$ unimodular matrix over the integers) with the maximal absolute value of entries ||A|| bounded by an integer $\lambda$ from above, the authors study the probability that the $m\times n$ matrix extended from $\bm{A}$ by appending other $m-k$ row vectors of dimension $n$ with entries chosen randomly and independently from the uniform distribution over $\{0,1,…{\lambda-1}\}$ is still primitive. The authors present a complete and rigorous proof of a lower bound on the probability, which is at least a constant for fixed $m$ in the range $[k+1, n-4]$. As an application, the authors prove that there exists a fast Las Vegas algorithm that completes a $k\times n$ primitive matrix $\bm{A}$ to an $n\times n$ unimodular matrix within expected Õ $(n^{w}\log||\mathit{\boldsymbol{A}}||)$ bit operations, where Õ is big-O but without log factors, $\omega$ is the exponent on the arithmetic operations of matrix multiplication.
  • CAO Wei
    Journal of Systems Science & Complexity. 2024, 37(4): 1772-1788. https://doi.org/10.1007/s11424-024-2500-1
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    Wan and Zhang (2021) obtained a nontrivial lower bound for the number of zeros of complete symmetric polynomials over finite fields, and proposed a problem whether their bound can be improved. In this paper, the author improves Wan-Zhang's bound from three aspects. The proposed results are based on the estimates related to the number of certain permutations and the value sets of non-permutation polynomials associated to the complete symmetric polynomial. And the author believes that there are still possibilities to improve the bounds and hence Wan-Zhang's bound.