Coal is essential to ensure China’s energy security. The sudden or gradual change of coal price reflects the degree of disequilibrium or expected disequilibrium of coal supply and demand, which will not be conducive to energy security. Therefore, it is important to analyze the change points of coal price and explore the reason of the price fluctuation. This paper analyses the coal price from January

This paper mainly studies the strong convergence properties for weighted sums of extended negatively dependent (END, for short) random variables. Some sufficient conditions to prove the strong law of large numbers for weighted sums of END random variables are provided. In particular, the authors obtain the weighted version of Kolmogorov type strong law of large numbers for END random variables as a

Currently, working with partially observed functional data has attracted a greatly increasing attention, since there are many applications in which each functional curve may be observed only on a subset of a common domain, and the incompleteness makes most existing methods for functional data analysis ineffective. In this paper, motivated by the appealing characteristics of conditional quantile regression

This paper extends the notion of μ-bases to arbitrary univariate polynomial matrices and present an efficient algorithm to compute a μ-basis for a univariate polynomial matrix based on polynomial matrix factorization. Particularly, when applied to polynomial vectors, the algorithm computes a μ-basis of a rational space curve in arbitrary dimension. The authors perform theoretical complexity analysis

The problem of designing a passive filter for nonlinear switched singularly perturbed systems with parameter uncertainties is explored in this paper. Firstly, the multiple-time-scale phenomenon is settled effectively by introducing a singular perturbation parameter in the plant. Secondly, the interval type-2 fuzzy set theory is employed where parameter uncertainties are expressed in membership functions

The \({\cal G}\)-SGD algorithm significantly outperforms the conventional SGD algorithm in ReLU neural networks by adopting the basis path set. However, how the inner mechanism of basis paths works remains mysterious, and the \({\cal G}\)-SGD algorithm that helps to find a basis path set is heuristic. This paper employs graph theory to investigate structure properties of basis paths in a more general

Mixed-integer optimal control problems (MIOCPs) usually play important roles in many real-world engineering applications. However, the MIOCP is a typical NP-hard problem with considerable computational complexity, resulting in slow convergence or premature convergence by most current heuristic optimization algorithms. Accordingly, this study proposes a new and effective hybrid algorithm based on quantum

This paper investigates the distributed convex optimization problem over a multi-agent system with Markovian switching communication networks. The objective function is the sum of each agent’s local nonsmooth objective function, which cannot be known by other agents. The communication network is assumed to switch over a set of weight-balanced directed graphs with a Markovian property. The authors propose

This paper presents a Q-learning-based target selection algorithm for spacecraft autonomous navigation using bearing observations of known visible targets. For the considered navigation system, the position and velocity of the spacecraft are estimated using an extended Kalman filter (EKF) with the measurements of inter-satellite line-of-sight (LOS) vectors obtained via an onboard star camera. This

This paper is concerned with the event-triggered L1-gain control of a class of nonlinear positive switched systems. First, an event-triggering condition in the form of 1-norm is presented for the systems. By virtue of the event-triggering strategy, the original system is transformed into an interval uncertain system. An event-triggered L1-gain controller is designed by decomposing the controller gain

This paper is devoted to investigating the dynamic output feedback (DOF) control problem of Markovian jump neutral-type stochastic systems with a guaranteed cost function. Both of the state and measurement equations contain time delays. Mode-dependent DOF controllers are first designed such that the closed-loop system is asymptotically stable in mean-square and an adequate performance level of this

This paper investigates the stabilization issue for a class of sampled-data nonlinear Markov switching system with indistinguishable modes. In order to handle indistinguishable modes, the authors reconstruct the original mode space by mode clustering method, forming a new merged Markov switching system. By specifying the difference between the Euler-Maruyama (EM) approximate discrete-time model of

This paper presents an algorithm to compute the topology of an algebraic space curve. This is a modified version of the previous algorithm. Furthermore, the authors also analyse the bit complexity of the algorithm, which is \(\widetilde{\cal O}\left( {{N^{20}}} \right)\), where N = max{d, τ}, d and τ are the degree bound and the bit size bound of the coefficients of the defining polynomials of the

Biological systems can be modeled and described by biological networks. Biological networks are typical complex networks with widely real-world applications. Many problems arising in biological systems can be boiled down to the identification of important nodes. For example, biomedical researchers frequently need to identify important genes that potentially leaded to disease phenotypes in animal and

Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and may be correlated for subjects coming from the same cluster. This paper presents a robust semiparametric transformation mixed effect models to analyze such data and use a U-statistic based

This paper proposes a finite-time consensus control algorithm based on nonlinear integral sliding-mode control for second-order multi-agent systems (MASs) with mismatched and matched disturbances. Firstly, a nonlinear finite-time disturbance observer is established to estimate the states and mismatched disturbances of the agent. Secondly, a dynamic integral sliding-mode (ISM) surface is designed by

Panel count data are frequently encountered when study subjects are under discrete observations. However, limited literature has been found on variable selection for panel count data. In this paper, without considering the model assumption of observation process, a more general semiparametric transformation model for panel count data with informative observation process is developed. A penalized estimation

In clinical and epidemiologic studies of time to event, the treatment effect is often of direct interest, and the treatment effect is not constant over time. In this paper, the authors propose an estimator for the cumulative hazard difference under a stratified additive hazards model. The asymptotic properties of the resulting estimator are established, and the finite-sample properties are examined

This paper firstly analyzes the Brexit’s impact on the US stock market using a novel interval methodology. The interval-valued dummy variables are proposed to measure the direction and magnitudes of the changes in the inter-day trend and the intra-day volatility of S&P500 returns simultaneously. It is found that both the trend and the volatility of S&P500 returns increased before the Brexit. Besides

This paper is focused on a distributed optimal control design for a class of nonlinear time-delay systems with delayed measurements and communication disruptions. The innovation lies in three aspects. The distributed optimal control method which includes an optimal controller and a bounded controller is designed based on Lyapunov function. The availability of data transmitted through the communication

Cyber-physical systems integrate computing, network and physical environments to make the systems more efficient and cooperative, and have important and extensive application prospects, such as the Internet of things. This paper studies the control problem of nonlinear cyber-physical systems with unknown dynamics and communication delays. A networked learning predictive control scheme is proposed for

The Global Entrepreneurship and Development Institute annually publishes the Global Entrepreneurship Index (GEI) to show entrepreneurship of each country/area. The GEI is obtained by averaging the scores of three sub-indexes, entrepreneurial attitudes, entrepreneurial abilities and Entrepreneurial aspirations. However, this GEI construction method with equal weights for three subindexes may be controversial

Complexity is commonly summarized as ‘the actions of the whole are more than the sum of the actions of the parts’. Understanding how the coherence emerges from these natural and artificial systems provides a radical shift in the process of thought, and brings huge promises for controlling and fostering this emergence. The authors define the term ‘Complex System Engineering’ to denote this approach

In optical networks without optical amplifiers (ONWOAs) photons may fade or fail to be detected, but new photons cannot be generated. Hence, under normal conditions, only 1→0 errors can occur. However, in some situations, the photodetector may generate a false 0→1 error. This mostly occurs in cases when the dark current is higher than specified. With this in mind, in this paper, the authors present

The models of competitive neural network (CNN) was in recent past proposed to describe the dynamics of cortical cognitive maps with unsupervised synaptic modifications, where there are two types of memories: Long-term memories (LTM) and short-term memories (STM), LTM presents unsupervised and slow synaptic modifications and STM characterize the fast neural activity. This paper is concerned with a class

This paper derives necessary and sufficient conditions of optimality in the form of a stochastic maximum principle for relaxed and strict optimal control problems with jumps. These problems are governed by multi-dimensional forward-backward doubly stochastic differential equations (FBDSDEs) with Poisson jumps and has firstly relaxed controls, which are measure-valued processes, and secondly, as an

This paper considers the drive-response synchronization in finite-time and fixed-time of inertial neural networks with time-varying and distributed delays (mixed delays). First, by constructing a proper variable substitution, the original inertial neural networks can be rewritten as a first-order differential system. Second, by constructing Lyapunov functions and using differential inequalities, some

This paper focuses on the problem of delay-dependent stability of linear systems with time-varying delay. A new delay-product-type augmented Lyapunov-Krasovskii functional (LKF) is constructed. Based on the LKF and by employing a generalized free-matrix-based integral inequality, less conservative delay-dependent stability criteria are obtained. Finally, two well-known numerical examples are used to

Input-output (Leontief) production function is widely used in economic analysis. And diminishing marginal rate of return is a very well accepted economic fact. Leontief production function normally results in a linear production possibility frontier (PPF) due to its linear feature, whereas diminishing marginal rate of return implies a non-linear PPF. In this paper, the authors aim to fix this problem

This paper considers tests for regression coefficients in high dimensional partially linear Models. The authors first use the B-spline method to estimate the unknown smooth function so that it could be linearly expressed. Then, the authors propose an empirical likelihood method to test regression coefficients. The authors derive the asymptotic chi-squared distribution with two degrees of freedom of

The control and scheduling for wireless networked control system with packet dropout and disturbance are investigated. A prediction based event triggered control is proposed to reduce data transmissions while preserving the robustness against external disturbance. First, a trigger threshold is especially designed to maintain the difference of the estimated and actual states below a proper boundary

In this paper, by the notions of base functionals and augmented dual cones, the authors indicate firstly that the norms, Gerstewitz functionals and oriented distance functions have common characteristics with base functionals. After that, the equivalence of these three sublinear functions on the ordering cone is established by using the structures of augmented dual cones under the assumption that it

A Japanese candlestick chart consists of not only the closing price but also the high, low and opening price information. Using the Japanese candlestick, this paper investigates the forecasting power of the shadow in Japanese candlestick chart. Empirical studies performed with the US stock market show that 1) there is a significant Halloween effect in the shadow; 2) shadow is valuable for predicting

A disturbance observer (DOB) based-backstepping sliding mode control scheme is discussed for a class of semi-strict nonlinear system with unknown parameters and mismatched uncertainty. Firstly, adaptive technique and DOB are respectively applied to tackle the unknown parameters and mismatched uncertainty, where the DOB can effectively alleviate the chattering problem of sliding mode control (SMC).

This paper proposes a new sure independence screening procedure for high-dimensional survival data based on censored quantile correlation (CQC). This framework has two distinctive features: 1) Via incorporating a weighting scheme, our metric is a natural extension of quantile correlation (QC), considered by Li (2015), to handle high-dimensional survival data; 2) The proposed method not only is robust

In the classical theory of self-tuning regulators, it always requires that the conditional variances of the systems noises are bounded. However, such a requirement may not be satisfied when modeling many practical systems, and one significant example is the well-known ARCH (autoregressive conditional heteroscedasticity) model in econometrics. The aim of this paper is to consider self-tuning regulators

The authors propose a two-step test for the two-sample problem of processes of Ornstein-Uhlenbeck type. In the first step, the authors test the equality of correlation structures, based on the least square estimators of the correlation parameters, and the test statistic follows the standard normal distribution. If the null hypothesis is not rejected in the first step, the authors consider a second

Quad-rotor unmanned aerial vehicle (UAV) is a typical multiple-input-multiple-output underactuated system with couplings and nonlinearity. Usually, the flying environment is very complex, so that it is impossible for the UAV to avoid effects derived from disturbances and uncertainties. In order to improve the reliability of flight control, we established the dynamic model of quad-rotor UAV by Newton-Euler

The formation of public opinion on the network is a hot issue in the field of complex network research, and some classical dynamic models are used to solve this problem. The signed network is a particular form of the complex network, which can adequately describe the amicable and hostile relationships in complex real-world systems. However, the methods for studying the dynamic process of public opinion

In this paper, linear quadratic (LQ) optimal control problems are investigated for two types of uncertain random systems which consider the coefficient of the perturbed term as a constant vector or a vector-valued function of state vector and control vector. First, the uncertain random optimal control model is established under expected value criterion. Second, based on Bellman’s principle, recurrence

This paper extends a method, called bilinear neural network method (BNNM), to solve exact solutions to nonlinear partial differential equation. New, test functions are constructed by using this method. These test functions are composed of specific activation functions of single-layer model, specific activation functions of “2-2” model and arbitrary functions of “2-2-3” model. By means of the BNNM,

Community structure is an integral characteristic of real world networks whichever processes or areas they emerge from. This paper addresses the problem of community structure detection theoretically as well as computationally. The authors introduce a number of concepts such as the neighbourhood and strength of a subgraph, p-community, local maximal p-community, hubs, and outliers that play elemental

The economy as a whole and most of its constituent parts, like markets, government institutions, firms, or households, are inherently complex conceptual constructions. Micro-level diversity, decentralized interaction, self-organization, adaptation and learning, emergence, and evolution, are some of the fundamental features that the above entities share and that allow to classify them as being complex

Based on the rational univariate representation of zero-dimensional polynomial systems, Tan and Zhang proposed the rational representation theory for solving a high-dimensional polynomial system, which uses so-called rational representation sets to describe all the zeros of a high-dimensional polynomial system. This paper is devoted to giving an improvement for the rational representation. The idea

Markov Chain Monte Carlo (MCMC) requires to evaluate the full data likelihood at different parameter values iteratively and is often computationally infeasible for large data sets. This paper proposes to approximate the log-likelihood with subsamples taken according to nonuniform subsampling probabilities, and derives the most likely optimal (MLO) subsampling probabilities for better approximation

This paper investigates sampling dependent stability for aperiodic sampled-data systems by employing a Lyapunov-like functional that is time-dependent, and not imposed to be definite positive. Based on the system information on the sampling interval wholly rather than partly, a new Lyapunov-like functional is constructed, which extends existing ones by introducing the integral of the system state and

As system identification theory and model predictive control are belonged to two different research fields separately, so one gap exists between these two subjects. To alleviate this gap between them, one new idea proposed in this paper is to introduce system identification theory into model predictive control. As the most important element in model predictive control is the prediction of the output

This paper proposes a kernel estimator for the coefficient of multidimensional time-varying diffusion processes as an extension of the estimation model for one dimensional diffusion coefficient to the multidimensional case. By using “time division”, the authors overcome the problem of sample observation in time varying model. In addition, the authors prove the strong consistency and limit distribution

The shaping of a limit order book illustrates the dynamics of the trading process, the changing pattern of the execution probability of limit orders therefore plays an important role. This paper presents a computable execution probability model for limit order market, as well as a numerical example that intuitively characterizes the changing pattern of the execution probability. The common effects

This paper is concerned with a linear-quadratic (LQ) stochastic Stackelberg differential game with one leader and two followers, where the game system is governed by a mean-field stochastic differential equation (MF-SDE). By maximum principle and verification theorem, the open-loop Stackelberg solution is expressed as a feedback form of the state and its mean with the help of three systems of Riccati

Multi-switching synchronization (MSS) of multiple different orders unknown chaotic (UC) systems confines hacking in the digital transmission process. Similarly, the suppression of undesirable chattering increases synchronization performance. This paper proposes a new robust synchronization control (RASC) technique and discusses the MSS of multiple different orders UC systems. This controller accomplishes

This paper presents the isogeometric least-squares collocation (IGA-L) method, which determines the numerical solution by making the approximate differential operator fit the real differential operator in a least-squares sense. The number of collocation points employed in IGA-L can be larger than that of the unknowns. Theoretical analysis and numerical examples presented in this paper show the superiority

The stabilization problem for the Schrödinger equation with an input time delay is considered from the view of system equivalence. First, a linear transform from the original system into an exponentially stable system with arbitrary decay rate, also called “target system”, is introduced. The linear transform is constructed via a kind of Volterra-type integration with singular kernels functions. As

This paper studies the optimal output tracking control and stabilization for networked control systems with packet losses via output feedback control. Both finite-horizon and infinite-horizon cases are considered. For the finite-horizon case, the authors introduce an augmented system according to the state variable and the reference trajectory for the first time. Based on a set of difference Riccati

The scheduling and control of a class of wireless networked control system is investigated, whose control loop is closed via a shared IEEE 802.15.4 wireless network. By using a gain scheduler within the packet-based control framework and fitting the delay-dependent gains into a time-delay system model, a less conservative self-triggered approach is proposed to determine the sampling update, which consequently

The studying motivation of this paper is that there exist many modeling issues of non-uniformly sampling nonlinear systems in industrial systems. Based on multi-model modeling principle, the corresponding model of non-uniformly sampling nonlinear systems is described by the nonlinear weighted combination of some linear models at local working points. Fuzzy modeling based on multimodel scheme is a common

In 2014, Chen and Singer solved the summability problem of bivariate rational functions. Later an algorithmic proof was presented by Hou and the author. In this paper, the algorithm will be simplified and adapted to the q-case.

Random variables and uncertain variables are respectively used to model randomness and uncertainty. While randomness and uncertainty always coexist in a same complex system. As an evolution of random variables and uncertain variables, uncertain random variable is introduced as a tool to deal with complex phenomena including randomness and uncertainty simultaneously. For uncertain random variables,

Empirical-likelihood-based inference for parameters defined by the general estimating equations of Qin and Lawless (1994) remains an active research topic. When the response is missing at random (MAR) and the dimension of covariate is not low, the authors propose a two-stage estimation procedure by using the dimension-reduced kernel estimators in conjunction with an unbiased estimating function based

This paper deals with H∞ control problem for nonlinear conformable fractional order systems. The authors first derive new sufficient condition for exponential stability of nonlinear conformable fractional order systems based on Lyapunov-like function method for conformable fractional order systems and linear matrix inequalities (LMIs) approach. Then, by introducing a new concepts of H∞ control problem