Table of Content

    25 October 2022, Volume 35 Issue 5
    Lithology Classification Based on Set-Valued Identification Method
    LI Jing, WU Lifang, LÜ Wenjun, WANG Ting, KANG Yu, FENG Deyong, ZHOU Hansheng
    2022, 35(5):  1637-1652.  DOI: 10.1007/s11424-022-1059-y
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    Lithology classification using well logs plays a key role in reservoir exploration.This paper studies the problem of lithology identification based on the set-valued method (SV),which uses the SV model to establish the relation between logging data and lithologic types at a certain depth point.In particular,the system model is built on the assumption that the noise between logging data and lithologic types is normally distributed,and then the system parameters are estimated by SV method based on the existing identification criteria.The logging data of Shengli Oilfield in Jiyang Depression are used to verify the effectiveness of SV method.The results indicate that the SV model classifies lithology more accurately than the Logistic Regression model (LR) and more stably than uninterpretable models on imbalanced dataset.Specifically,the Macro-F1 of the SV models (i.e.,SV (3),SV (5),and SV (7)) are higher than 85%,where the sandstone samples account for only 22%.In addition,the SV (7) lithology identification system achieves the best stability,which is of great practical significance to reservoir exploration.
    Pinning Synchronization of Coupled Oscillators with Paired Topologies
    ZHANG Miaosen, LÜLU Yuezu, WANG Qishao, WEN Guanghui, LIU Guohua, XU Wenying
    2022, 35(5):  1653-1667.  DOI: 10.1007/s11424-022-1043-6
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    This paper investigates the pinning synchronization of a group of coupled oscillators,where both the dissipative and restorative interactions are taken into consideration.The paired coupling topologies are introduced to capture this feature of the dynamics.To realize the synchronization of the coupled oscillators,the pinning control is introduced,and two pinning criteria are proposed to ensure the synchronization.Both these two proposed criteria provide sufficient and necessary conditions for pinning synchronization of the coupled oscillators with paired topologies.Simulation examples are illustrated to verify the proposed theoretical results.
    Detection of Stealthy False Data Injection Attacks Against Cyber-Physical Systems:A Stochastic Coding Scheme
    GUO Haibin, PANG Zhonghua, SUN Jian, LI Jun
    2022, 35(5):  1668-1684.  DOI: 10.1007/s11424-022-1005-z
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    This paper,from the view of a defender,addresses the security problem of cyber-physical systems (CPSs) subject to stealthy false data injection (FDI) attacks that cannot be detected by a residual-based anomaly detector without other defensive measures.To detect such a class of FDI attacks,a stochastic coding scheme,which codes the sensor measurement with a Gaussian stochastic signal at the sensor side,is proposed to assist an anomaly detector to expose the FDI attack.In order to ensure the system performance in the normal operational context,a decoder is adopted to decode the coded sensor measurement when received at the controller side.With this detection scheme,the residual under the attack can be significantly different from that in the normal situation,and thus trigger an alarm.The design condition of the coding signal covariance is derived to meet the constraints of false alarm rate and attack detection rate.To minimize the trace of the coding signal covariance,the design problem of the coding signal is converted into a constraint non-convex optimization problem,and an estimation-optimization iteration algorithm is presented to obtain a numerical solution of the coding signal covariance.A numerical example is given to verify the effectiveness of the proposed scheme.
    Tracking Control of Uncertain High-Order Nonlinear Systems with Odd Rational Powers and the Dead-Zone Input:A Direct Fuzzy Adaptive Control Method
    LIU Zhenguo, SHI Yuyuan, WU Yuqiang
    2022, 35(5):  1685-1699.  DOI: 10.1007/s11424-022-1011-1
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    This work studies the tracking issue of uncertain nonlinear systems.The existence of odd rational powers,multiple unknown parameters and the dead-zone input add many difficulties for control design.During procedures of the control design,by introducing an appropriate Lyapunov function,utilizing recursive control method and the inequality technique,some appropriate intermediate auxiliary control laws are designed under the hypothesis that nonlinear terms in the system are known.When those nonlinear terms are unknown,by employing the powerful approximation ability of fuzzy systems,the intermediate auxiliary control laws are approximated recursively and used to construct the virtual control.Finally,a new fuzzy adaptive tracking controller is constructed to ensure a small tracking error and the boundedness of all states.In this paper,the overparameterization problem is significantly avoided since only two adaptive laws are adopted.Numerical and practical examples are used to verify the raised theory.
    Adaptive Event-Triggering Consensus for Multi-Agent Systems with Linear Time-Varying Dynamics
    ZHANG Wenbing, ABUZAR HUSSEIN MOHAMMED Atitalla, BAO Jiatong, LIU Yurong
    2022, 35(5):  1700-1718.  DOI: 10.1007/s11424-022-1065-0
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    In this paper,the authors study the fully distributed event-triggering consensus problem for multi-agent systems with linear time-varying dynamics,where each agent is described by a linear time-varying system.An adaptive event-triggering protocol is proposed for time-varying multi-agent systems under directed graph.Based on the Gramian matrix of linear time-varying systems,the design of control gain is done and sufficient conditions ensuring the consensus of linear time-varying multiagent systems are obtained.It is shown that the coupling strength is closely related to the triggering condition.When it comes to undirected graph,it is shown that the coupling strength is independent on the triggering condition and thus the design procedure is of more freedom than the directed case.In addition,it is also proved that Zeno behaviours can be excluded in the proposed protocols.A numerical example is presented to demonstrate the effectiveness of the theoretical results.
    Trajectory Tracking Control of Euler-Lagrange Systems with ISS-Like Robustness to Actuator Noises
    WU Haiwen, XU Dabo
    2022, 35(5):  1719-1747.  DOI: 10.1007/s11424-022-0219-4
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    This paper studies global robust tracking of uncertain Euler-Lagrange systems with input disturbances.The authors develop a robust regulation-based approach for the problem.Specifically,by introducing a novel nonlinear internal model,the authors solve global asymptotic trajectory tracking with disturbance rejection of multiple step/sinusoidal signals with unknown amplitudes,frequencies,and phases.Moreover,the authors show that a robustness property to actuator noises can be guaranteed in a sense of strong integral input-to-state stability (iISS).That is,the closed-loop system is not only iISS but also input-to-state stable (ISS) to small magnitude actuator noises.Furthermore,the authors explore a by-product overparametrized linear regression estimation,coming up with robust estimation of the unknown parameters.Finally,the authors present several numerical examples to illustrate the theoretical results.
    Fixed-Time Synchronization of Complex Networks via Intermittent Control Without Sign Function
    GAO Jie, ZHAO Junchan
    2022, 35(5):  1748-1760.  DOI: 10.1007/s11424-022-1016-9
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    This paper investigates the fixed-time synchronization problem of complex networks.A novel switching controller is proposed to solve the problem.The designed controller in this paper only needs intermittently to pin a few of nodes,which could reduce the control time and save the system's energy.Moreover,compared with the existing control methods for the fixed-time synchronization,the novel controller does not use the sign function,which could avoid the chattering behaviors.By constructing a Lyapunov function and designing a comparison system,some sufficient conditions are obtained to achieve the fixed-time synchronization.Finally,the numerical simulations could verify the effectiveness and feasibility of the proposed control approaches.
    Fuzzy Filter Design for Affine Systems with Sensor Faults:A Dynamic Event-Triggered Approach
    CHENG Jun, WU Yuyan, WU Zhengguang, LI Kezan
    2022, 35(5):  1761-1784.  DOI: 10.1007/s11424-022-1071-2
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    This study addresses the issue of dynamic event-triggered-based filtering for fuzzy affine systems.To alleviate the utilization of constraint bandwidth resources and improve the efficiency of the signals exchange,a dynamic event-triggered protocol is forwarded to regulate the trigger instants with objective system states.Meanwhile,the nonhomogeneous Markov process is proposed to characterize the dynamic behaviors of sensor faults,where the time-varying transition probabilities belong to a convex polytope set.Finally,the validity and applicability of devised filter design methodology for fuzzy affine systems are displayed via two practical models.
    Robust H Control of Switched Nonlinear Systems Under Sampled Data
    ZHAO Hongpeng, WANG Xingtao
    2022, 35(5):  1785-1807.  DOI: 10.1007/s11424-022-1039-2
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    This paper investigates the globally asymptotically stable and L2-gain of robust H control for switched nonlinear systems under sampled data.By considering the relationship between the sampling period and the dwell time,the non-switching and one switching are discussed in the sampling interval,respectively.Firstly,a state feedback sampled-data controller is constructed by the back-stepping method,and the switching converts to asynchronous switching if it happens within the sampling interval.Then,under the limiting conditions of the sampling period,which are obtained by the average dwell time method,the closed-loop system is globally asymptotically stable and has L2-gain.Finally,two numerical examples are provided to demonstrate the effectiveness of the proposed method.
    Matching Algorithms of Minimum Input Selection for Structural Controllability Based on Semi-Tensor Product of Matrices
    FAN Naqi, ZHANG Lijun, ZHANG Shenggui, LIU Jiuqiang
    2022, 35(5):  1808-1823.  DOI: 10.1007/s11424-022-1178-5
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    In 2011,Liu,et al.investigated the structural controllability of directed networks.They proved that the minimum number of input signals,driver nodes,can be determined by seeking a maximum matching in the directed network.Thus,the algorithm for seeking a maximum matching is the key to solving the structural controllability problem of directed networks.In this study,the authors provide algebraic expressions for matchings and maximum matchings proposed by Liu,et al.(2011) via a new matrix product called semi-tensor product,based on which the corresponding algorithms are established to seek matchings and maximum matchings in digraphs,which make determining the number of driver nodes tractable in computer.In addition,according to the proposed algorithm,the authors also construct an algorithm to distinguish critical arcs,redundant arcs and ordinary arcs of the directed network,which plays an important role in studying the robust control problem.An example of a small network from Liu's paper is used for algorithm verification.
    Adaptive Asymptotic Tracking Control for Stochastic Nonlinear Systems with Unknown Backlash-Like Hysteresis
    WANG Le, SUN Wei, WU Yuqiang
    2022, 35(5):  1824-1838.  DOI: 10.1007/s11424-022-1111-y
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    In this study,an adaptive asymptotic tracking control problem is considered for stochastic nonlinear systems with unknown backlash-like hysteresis.By utilizing backstepping technology and bound estimation approach,an adaptive asymptotic tracking control scheme is designed,where fuzzy systems are applied to approximate unknown function terms,the effect of hysteresis and stochastic disturbances is compensated appropriately.The proposed scheme ensures that the tracking error can asymptotically converge to zero in probability and all signals of the closed-loop system are bounded almost surely.Finally,the effectiveness of the control scheme is verified by giving a simulation example.
    Foreign Trade Survey Data:Do They Help in Forecasting Exports and Imports?
    BAI Yun, WANG Shouyang, ZHANG Xun
    2022, 35(5):  1839-1862.  DOI: 10.1007/s11424-022-1015-x
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    Business survey,which starts from the microeconomic level,is a widely used short-term forecasting tool in practice.In this study,the authors examine whether foreign trade survey data collected by China's Ministry of Commerce would provide reliable forecasts of China's foreign trade.The research procedure is designed from three perspectives including forecast information test,turning point forecast,and out-of-sample value forecast.First,Granger causality test detects whether survey data lead exports and imports.Second,business cycle analysis,a non-model based method,is performed.The authors construct composite indexes with business survey data to forecast turning points of foreign trade.Third,model-based numerical forecasting methods,including the Autoregressive Integrated Moving Average Model with Exogenous Variables (ARIMAX) and the artificial neural networks (ANNs) models are estimated.Empirical results show that survey data granger cause imports and exports,the leading composite index provides signal for changes of trade cycles,and quantitative models including survey data generate more accurate forecasts than benchmark models.It is concluded that trade survey data has excellent predictive capabilities for imports and exports,which can offer some priorities for government policy-making and enterprise decision making.
    Illiquidity Comovement and Market Crisis
    ZENG Qingduo, ZHANG Qiang, LIU Shancun, YANG Yaodong
    2022, 35(5):  1863-1874.  DOI: 10.1007/s11424-022-0299-1
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    This paper presents a rational expectation equilibrium model to explore how the financial contagion occurs between the unlinked markets that do not share common fundamentals.In the proposed model,the authors assume two of the three risky assets share no common fundamental factors,but are connected by one intermediate asset via cross fundamentals.Through this channel,investors transmit fundamental risk from one asset to another by dint of the cross fundamentals.This mechanism causes liquidity comovement and subsequently becomes a source of market crisis:Through the contagion mechanism,an initial liquidity shock in one asset can result in a drop tendency in liquidity and price informativeness for another asset.Such comovement in liquidity offers a new explanation for idiosyncratic assets in financial contagion.
    Model Averaging Multistep Prediction in an Infinite Order Autoregressive Process
    YUAN Huifang, LIN Peng, JIANG Tao, XU Jinfeng
    2022, 35(5):  1875-1901.  DOI: 10.1007/s11424-022-0311-9
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    The key issue in the frequentist model averaging is the choice of weights.In this paper,the authors advocate an asymptotic framework of mean-squared prediction error (MSPE) and develop a model averaging criterion for multistep prediction in an infinite order autoregressive (AR (∞)) process.Under the assumption that the order of the candidate model is bounded,this criterion is proved to be asymptotically optimal,in the sense of achieving the lowest out of sample MSPE for the samerealization prediction.Simulations and real data analysis further demonstrate the effectiveness and the efficiency of the theoretical results.
    A Tight Approximation Algorithm for Multi-Vehicle CVRP with Unsplittable Demands on a Line
    WU Yuanxiao, LU Xiwen
    2022, 35(5):  1902-1909.  DOI: 10.1007/s11424-022-0280-z
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    In this paper,the authors study the multi-vehicle capacitated vehicle routing problem on a line-shaped network with unsplittable demand.The objective is to find a transportation scheme to minimize the longest distance traveled by a single vehicle such that all the customers are served without violating the capacity constraint.The authors show that this problem has no polynomialtime algorithm with performance ratio less than 2 on condition that PNP,and then provide a 2-approximation algorithm.
    A Projection Approach to Monotonic Regression with Bernstein Polynomials
    ZHU Guo, FANG Xiangzhong
    2022, 35(5):  1910-1928.  DOI: 10.1007/s11424-022-0321-7
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    Monotonic regression problems have been widely seen in many fields like economics and biostatistics.Usually the monotonic parameter space is used by the Bayesian methods using Bernstein polynomials.In this paper the authors extend the usual parameter space to a larger space in which all the proper parameters making the regression function to be monotonic are included.In order to ensure that the problem could be solved in the new parameter space,the authors use a projection posterior method to make inference.The authors show the proposed method has good approximation properties and performs well compared with other competing methods both in simulations and in practical applications.
    Outlier Detection via a Block Diagonal Product Estimator
    LI Chikun, JIN Baisuo
    2022, 35(5):  1929-1943.  DOI: 10.1007/s11424-022-0298-2
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    Outlier detection is a fundamental topic in robust statistics.Traditional outlier detection methods try to find a clean subset of given size,which is used to estimate the location vector and scatter matrix,and the outliers can be flagged by the Mahalanobis distance.However,methods such as the minimum covariance determinant approach cannot be applied directly to high-dimensional data,especially when the dimension of the sample is greater than the sample size.A novel fast detection procedure based on a block diagonal partition is proposed,and the asymptotic distribution of the modified Mahalanobis distance is obtained.The authors verify the specificity and sensitivity of this procedure by simulation and real data analysis in high-dimensional settings.
    Constructing the Basis Path Set by Eliminating the Path Dependency
    ZHU Juanping, MENG Qi, CHEN Wei, WANG Yue, MA Zhiming
    2022, 35(5):  1944-1962.  DOI: 10.1007/s11424-022-0208-7
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    The newly appeared$\mathcal{G}$-SGD algorithm can only heuristically find the basis path set in a simple neural network,so its generalization to a more practical network is hindered.From the perspective of graph theory,the BasisPathSetSearching problem is formulated to find the basis path set in a complicated fully connected neural network.This paper proposes algorithm DEAH to hierarchically solve the BasisPathSetSearching problem by eliminating the path dependencies.For this purpose,the authors discover the underlying cause of the path dependency between two independent substructures.The path subdivision chain is proposed to effectively eliminate the path dependency,both inside the chain and between chains.The theoretical proofs and the analysis of time complexity are presented for Algorithm DEAH.This paper therefore provides one methodology to find the basis path set in a general and practical neural network.
    Single-Index Quantile Regression with Left Truncated Data
    XU Hongxia, FAN Guoliang, LI Jinchang
    2022, 35(5):  1963-1987.  DOI: 10.1007/s11424-022-1118-4
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    The purpose of this paper is two fold.First,the authors investigate quantile regression (QR) estimation for single-index QR models when the response is subject to random left truncation.The random weights are introduced to deal with left truncated data and the associated iteration estimation method is proposed.The asymptotic properties for the proposed QR estimates of the index parameter and unknown link function are both obtained.Further,by combining the QR loss function and the adaptive LASSO penalization,a variable selection procedure for the index parameter is introduced and its oracle property is established.Second,a weighted empirical log-likelihood ratio of the index parameter based on the QR method is introduced and is proved to be asymptotic standard chi-square distribution.Furthermore,confidence regions of the index parameter can be constructed.The finite sample performance of the proposed methods are demonstrated.A real data analysis is also conducted to show the usefulness of the proposed approaches.
    Straightforward Guess and Determine Analysis Based on Genetic Algorithm
    CAO Chunping, CEN Zhe, FENG Xiutao, WANG Zhangyi, ZHU Yamin
    2022, 35(5):  1988-2003.  DOI: 10.1007/s11424-022-1031-x
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    With the development of artificial intelligence,the genetic algorithm has been widely used in many fields.In cryptography,the authors find it is natural to code an individual and design its fitness in a genetic algorithm for a straightforward guess and determine analysis (SGDA,in short).Based on this observation,the authors propose an SGDA based on genetic algorithm.Comparing it with the other three SGDAs based on exhaustive search,MILP method and CPP method respectively,the authors illustrate its effectiveness by three stream ciphers:Small scale SNOW 2.0,medium scale Enocoro-128v2 and large scale Trivium.The results show our method is significantly superior to them,especially for Trivium,the method can find a solution of 165 variables in less than one hour,while the other three methods are not applicable due to its enormous search space of size 2619.37.As far as we know,it is a best solution in an SGDA for Trivium so far.
    The Discrete Approximation Problem for a Special Case of Hermite-Type Polynomial Interpolation
    GONG Yihe, JIANG Xue, ZHANG Shugong
    2022, 35(5):  2004-2015.  DOI: 10.1007/s11424-022-1068-x
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    Every univariate Hermite interpolation problem can be written as a pointwise limit of Lagrange interpolants.However,this property is not preserved for the multivariate case.In this paper,the authors first generalize the result of P.Gniadek.As an application,the authors consider the discrete approximation problem for a special case when the interpolation condition contains all partial derivatives of order less than n and one nth order differential polynomial.In addition,for the case of n ≥ 3,the authors use the concept of Cartesian tensors to give a sufficient condition to find a sequence of discrete points,such that the Lagrange interpolation problems at these points converge to the given Hermite-type interpolant.
    Normalization of Indexed Differentials by Extending Gröner Basis Theory
    LIU Jiang, NI Feng, SONG Shihang, DU Mingjun
    2022, 35(5):  2016-2028.  DOI: 10.1007/s11424-021-0302-2
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    It is a fundamental problem to determine the equivalence of indexed differential polynomials in both computer algebra and differential geometry.However,in the literature,there are no general computational theories for this problem.The main reasons are that the ideal generated by the basic syzygies cannot be finitely generated,and it involves eliminations of dummy indices and functions.This paper solves the problem by extending Göbner basis theory.The authors first present a division of the set of elementary indexed differential monomials$E_{\part}$/into disjoint subsets,by defining an equivalence relation on$E_{\part}$/based on Leibniz expansions of monomials.The equivalence relation on$E_{\part}$/also induces a division of a Göbner basis of basic syzygies into disjoint subsets.Furthermore,the authors prove that the dummy index numbers of the sim-monomials of the elements in each equivalence class of$E_{\part}$/have upper bounds,and use the upper bounds to construct fundamental restricted rings.Finally,the canonical form of an indexed differential polynomial proves to be the normal form with respect to a subset of the Göbner basis in the fundamental restricted ring.