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In this paper, a peridynamic differential operator (PDDO) method is developed to analyze the static and dynamic responses of size-dependent elastic structures in the frame of a consistent couple stress theory (CCST). The displacement governing equations together with the boundary conditions of the couple-stress static problems are transformed from the local differential form to the nonlocal integral form through a fourth-order PDDO and then solved by a meshfree scheme. For dynamic cases, the time-domain problems are first transformed into frequency domain by Fourier transform, then solved by the PDDO meshless method in the frequency domain. The time-domain results are finally obtained by using an exponential window method (EWM). The size effects on the static and dynamic responses of some typical elastic problems are investigated by the developed PDDO method. A very high level of computational accuracy is achieved by comparing with the analytical solutions and the existing numerical results. [ABSTRACT FROM AUTHOR]

This study is focused on analyzing the L 1 -stochastic internal stability and the design of an L 1 -gain controller for two-dimensional (2D) continuous positive Markov jumping systems (PMJSs) with constraints on the inputs and states. An algorithm is developed to explicitly determine the state feedback control law with the optional L 1 -gain performance. First, by constructing a co-positive stochastic Lyapunov function for the positive system and establishing the equation for the Markov states' mathematical expectation, several sufficient and necessary conditions for L 1 -stochastic internal stability are derived. This analysis indicates that 2D PMJSs with directional delays are influenced by sizes of the system matrices and magnitude of delays, and transition matrix. Second, a method for calculating the L 1 -gain is formulated utilizing linear programming (LP), thus, an L 1 -gain controller is designed to guarantee that the closed-loop system is positive and L 1 -stochastically internally stable, while achieving optimal L 1 -gain performance. Two numerical and practical examples are considered, and the influence of delays and transition probability matrices on the L 1 -gain is specified to validate the preceding theoretical findings. [ABSTRACT FROM AUTHOR]

This paper investigates the problems of stability and decentralized control for a class of interconnected fractional-order systems. Firstly, model of the interconnected fractional-order system is established. In the meantime, a decentralized periodic intermittent control technique based on partial variables of the system is developed, and the time cost in the control process and the control cost can be saved by this technique. Secondly, stability criteria by using stability theory of fractional-order systems are derived, respectively. Related results can also be used for estimating regions of stability and applied to practical systems such as the power system, the wireless power transfer(WPT) system and the brushless DC motors (BLDCM) system. Besides, in order to reduce the conservatism of the results, the relevant inequality technique is introduced during the derivation process. At last, illustrative examples are given to demonstrate effectiveness of the obtained results. Compared with existing literatures, simulation results indicate that the conservatism of the results is decreased obviously, and the proposed control scheme can indeed save the time cost and the control cost. [ABSTRACT FROM AUTHOR]

This paper presents a new synchronization criterion with a hybrid control approach for multidirectional associative memory neural networks based on memristor (MMAMNNs). That is, the method of impulsive and feedback control combing with the (event) self-triggered mechanism is adopted. However some projective synchronization errors based on state related parameters of MMAMNNs will be affected by the diverse initial conditions. Thus, the new criterion is supported by establishing a novel Lyapunov function combined with the features of such diverse parameters and systems. A collaborative proposed method is designed to make the error of such system converging to zero. Then, the Zeno-behavior is testified to disappear from the proposed programs. Finally, some examples demonstrate the validity of the proposed method and to show its potential application in image protection. [ABSTRACT FROM AUTHOR]

This paper investigates the incipient fault-tolerant problem of heterogeneous multiagent systems and applies the proposed method to the wireless power transfer grid. Firstly, a novel extended state observer is designed for every follower system, which not only relative output information of its agent but also contains output information of neighboring agents. Then, a state estimation feedback control scheme is proposed to compensate for the time delay and incipient faults effectively. It is worth noting that the proposed observer-based control strategy distributes the weight of the output information error. Therefore, the observer has higher adjustability and more substantial applicability. Further, we make a consistent analysis of the system under the proposed control scheme with the Lyapunov–Krasovskii theory that the sufficient conditions can be formed for the stability of the system. Finally, the validity of the proposed control scheme is demonstrated through numerical and application examples. [ABSTRACT FROM AUTHOR]

This paper deals with issues of stochastic stability and decentralized control for interconnected fractional-order stochastic systems (IFSSs) with input saturation. At first, model of the IFSS is built. Meanwhile, a decentralized control technique in view of observer and partial state variables of the system is proposed. This method can simultaneously realize the observation and control for the system only by observing and controlling partial state variables. And both observation cost and control cost can also be decreased. Then, by means of fractional calculus theory, a novel stability analysis is shown, and relational stochastic stability criteria are derived. Related results can be applied not only to the common IFSSs, but also to many actual systems, for example power systems and chaotic systems. Additionally, range of the order for the IFSSs is also further enlarged. Eventually, validity of the results is verified via several numerical simulations, and advantages for the control technique developed are presented by comparison. • New stochastic stability results for the IFSS are developed. • A decentralized control approach based on observer and partial variables is proposed. • Compared with related papers, scope of order α i for the IFSS is enlarged. • Related results can also be extended to many real systems. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to detect edge of image in high noise level, suffering Gaussian noise. Design/methodology/approach - Canny edge detection algorithm performs poorly when applied to highly distorted images suffering from Gaussian noise. In Canny algorithm, 2D-gaussian function is used to remove noise and preserve edge. In high noise level, 2D-gaussian function cannot meet the needs. In this paper, an improving Canny edge detection algorithm is presented. The algorithm presented is based on local linear kernel smoothing, in which local neighborhoods are adapted to the local smoothness of the surface measured by the observed data. The procedure can therefore remove noise correctly in continuity regions of the surface, and preserve discontinuities at the same time. Findings - The statistical model of removing noise and preserving edge can meet the need of edge detection in images highly corrupted by Gaussian noise. Research limitations/implications - It was found that when the noise ratio is higher than 40 percent, the edge detection algorithm performs poorly. Practical implications - A very useful method for detecting highly distorted images suffering Gaussian noise. Originality/value - Since an image can be regarded as a surface of the image intensity function and such a surface has discontinuities at the outlines of objects, this algorithm can be applied directly to detect edge of image in high noise level. [ABSTRACT FROM AUTHOR]

• The syntactic structure of natural language is import for the model to understand the sentences comprehensively. • The relative syntactic distance can be used to describe the degree of dependency between adjacent words in a sentence. • A relative syntactic distance-based language model RSD-LSTM is proposed to integrate syntactic information into LSTM. • Low-level and high-level syntactic structure features can be fused to generate hidden representations. • The experimental results of RSD-LSTM outperform existing state-of-the-art models on different tasks. In natural language, the relationship among the constituents of a sentence is usually tree-like: words, phrases, and clauses constitute a sentence hierarchically, and the dependency between different constituents induces the syntactic structure. Such a complex tree-like structure is vital for understanding natural languages. However, recurrent neural networks (RNNs) model languages sequentially and fail to encode a hierarchical syntactic dependency comprehensively, therefore causing the networks to underperform on comprehension-based tasks. In this paper, we propose a novel neural language model, called relative syntactic distance LSTM (RSD-LSTM), to capture the syntactic structure dependency dynamically. RSD-LSTM employs a convolutional neural network to compute the relative syntactic distance between sentences to represent the degree of dependency between words and modifies the gating mechanism of LSTM through the relative syntactic distance. Furthermore, we add a direct connection between hidden states to fuse high-level and low-level syntactic features. We conducted extensive experiments on language modeling. The results suggest that RSD-LSTM achieves improvements of 1.82 and 2.03 in perplexity compared with current top methods on the Penn Treebank and WikiText-2 datasets, respectively. Moreover, we conducted experiments on a machine translation application task. Experimental results of this task also show significant improvements of RSD-LSTM compared with baseline models. [ABSTRACT FROM AUTHOR]