Synchronization Issues Research Articles

On-Orbit Geometric Calibration and Accuracy Validation of the Jilin1-KF01B Wide-Field Camera

On-orbit geometric calibration is key to improving the geometric positioning accuracy of high-resolution optical remote sensing satellite data. Grouped calibration with geometric consistency (GCGC) is proposed in this paper for the Jilin1-KF01B satellite, which is the world’s first satellite capable of providing 150-km swath width and 0.5-m resolution data. To ensure the geometric accuracy of high-resolution image data, the GCGC method conducts grouped calibration of the time delay integration charge-coupled device (TDI CCD). Each group independently calibrates the exterior orientation elements to address the multi-time synchronization issues between imaging processing system (IPS). An additional inter-chip geometric positioning consistency constraint is used to enhance geometric positioning consistency in the overlapping areas between adjacent CCDs. By combining image simulation techniques associated with spectral bands, the calibrated panchromatic data are used to generate simulated multispectral reference band image as control data, thereby enhancing the geometric alignment consistency between panchromatic and multispectral data. Experimental results show that the average seamless stitching accuracy of the basic products after calibration is better than 0.6 pixels, the positioning accuracy without ground control points(GCPs) is better than 20 m, the band-to-band registration accuracy is better than 0.3 pixels, the average geometric alignment consistency between panchromatic and multispectral data are better than 0.25 multispectral pixels, the geometric accuracy with GCPs is better than 2.1 m, and the geometric alignment consistency accuracy of multi-temporal data are better than 2 m. The GCGC method significantly improves the quality of image data from the Jilin1-KF01B satellite and provide important references and practical experience for the geometric calibration of other large-swath high-resolution remote sensing satellites.

Long-Run Behavior Estimation of Temporal Boolean Networks With Multiple Data Losses.

This brief devotes to investigating the long-run behavior estimation of temporal Boolean networks (TBNs) with multiple data losses, especially the asymptotical stability. The information transmission is modeled by Bernoulli variables, based on which an augmented system is constructed to facilitate the analysis. A theorem guarantees that the asymptotical stability of the original system can be converted to that of the augmented system. Subsequently, one necessary and sufficient condition is obtained for asymptotical stability. Furthermore, an auxiliary system is derived to study the synchronization issue of the ideal TBNs with normal data transmission and TBNs with multiple data losses, as well as an effective criterion for verifying synchronization. Finally, numerical examples are given to illustrate the validity of the theoretical results.

Synchronization Analysis of Discrete-Time Fractional-Order Quaternion-Valued Uncertain Neural Networks.

This article studies synchronization issues for a class of discrete-time fractional-order quaternion-valued uncertain neural networks (DFQUNNs) using nonseparation method. First, based on the theory of discrete-time fractional calculus and quaternion properties, two equalities on the nabla Laplace transform and nabla sum are strictly proved, whereafter three Caputo difference inequalities are rigorously demonstrated. Next, based on our established inequalities and equalities, some simple and verifiable quasi-synchronization criteria are derived under the quaternion-valued nonlinear controller, and complete synchronization is achieved using quaternion-valued adaptive controller. Finally, numerical simulations are presented to substantiate the validity of derived results.

Secure impulsive synchronization for derivatively coupled networks against DoS attacks: A memory-compensated strategy

This work is concerned with the synchronization issue of complex networks suffering from Denial-of-Service (DoS) attacks. The derivative coupling has been proposed to model the nodes which are capable of perceiving state changing. An overarching handling procedure is initially introduced to convert derivatively coupled dynamic networks into a general form. To offset the information missing resulting from DoS attacks, an intricately crafted memory-based self-triggered impulsive controller (MBSTIC) is devised. The introduced scheme involves the meticulous collection of nodes’ historical state information. By jointly considering Lyapunov stability theorem and mathematical deduction approach, sufficient conditions for ensuring synchronous behavior for controlled networks are derived. A numerical example is given to demonstrate that the proposed method exhibits considerable performance when facing DoS attacks.

Designing a switching law for Mittag-Leffler stability in nonlinear singular fractional-order systems and its applications in synchronization

In this work, the stability and synchronization issue of switched singular continuous-time fractional-order systems with nonlinear perturbation are examined. Using the fixed-point principle and S-procedure lemma, a sufficient condition for the existence and uniqueness of the solution to the switched singular fractional-order system is first stated. Next, using the Lyapunov functional method in combination with some techniques related to singular systems and fractional calculus, a switching rule for regularity, impulse-free, and Mittag-Leffler stability is developed based on the formation of a partition of the stability state regions in convex cones. For synchronizing switched fractional singular dynamical systems, we propose a state feedback controller that ensures regularity, impulse-free, and Mittag-Leffler stable in the error closed-loop system. Finally, the ease of use and computational convenience of our proposed methods are illustrated by two numerical examples and a practical example about DC motor controlling an inverted pendulum accompanied by simulation results.

Intermittent dynamic event-triggered control for synchronization of Takagi–Sugeno fuzzy competitive neural networks with leakage delay and different time scales

Because competitive neural networks (CNNs) can simulate the phenomena of lateral inhibition among neurons, their dynamics are attracting increasing attention, which motives us to investigate the global exponential synchronization issue of multiple time-delays fuzzy CNNs (MDFCNNs) with different time scales in this article. Firstly, to solve the significant resource wastage problem caused by the time-triggered mechanism previously adopted in CNNs, a novel intermittent dynamic event-triggered mechanism is proposed. It is worth mentioning that the fuzzy logic systems are also utilized in this model and controller, effectively handling the uncertainties and nonlinearities in practical problems. Secondly, by designing the intermittent static/dynamic event-triggered mechanism, we derive the global exponential synchronization conditions for MDFCNNs with different time scales under a simpler and more implementable controller composed of a linear negative feedback control term. We also utilize the reduction to absurdity to demonstrate the nonexistence of Zeno behavior for the error system of master-slave CNNs. Furthermore, we provide several corollaries to further indicate the generality of the model and the cost savings of the control mechanism. Finally, we provide an example and some comparisons to demonstrate the efficiency of the derived theoretical findings.

RenderKernel: High-level programming for real-time rendering systems

Real-time rendering applications leverage heterogeneous computing to optimize performance. However, software development across multiple devices presents challenges, including data layout inconsistencies, synchronization issues, resource management complexities, and architectural disparities. Additionally, the creation of such systems requires verbose and unsafe programming models. Recent developments in domain-specific and unified shading languages aim to mitigate these issues. Yet, current programming models primarily address data layout consistency, neglecting other persistent challenges.In this paper, we introduce RenderKernel, a programming model designed to simplify the development of real-time rendering systems. Recognizing the need for a high-level approach, RenderKernel addresses the specific challenges of real-time rendering, enabling development on heterogeneous systems as if they were homogeneous. This model allows for early detection and prevention of errors due to system heterogeneity at compile-time. Furthermore, RenderKernel enables the use of common programming patterns from homogeneous environments, freeing developers from the complexities of underlying heterogeneous systems. Developers can focus on coding unique application features, thereby enhancing productivity and reducing the cognitive load associated with real-time rendering system development.

Delay-compensatory synchronization on uncertain chaotic neural networks via average delayed impulsive gains

This paper mainly studies the exponential synchronization issue of chaotic neural networks with parametric uncertainties and time-varying delays via hybrid impulsive control and delay compensatory strategy. Considering the hybrid impulses and flexible delays in the controller, the idea of average delayed impulsive gain (ADIG) is introduced to quantify the effects of hybrid impulses from a comprehensive viewpoint, i.e., not only the desynchronizing/synchronizing delay-free impulses but also the desynchronizing/synchronizing delayed impulses are discussed. Meanwhile, the impulsive delays are fetched and integrated to compensate the desynchronizing impulses dynamically, which removes certain strict restrictions on the impulsive gains and impulsive delays compared with existed works. Correspondingly, some relaxed sufficient criteria for exponential synchronization are derived by jointly utilizing the concept of average delayed impulsive gain, the delay compensatory scheme and the mathematical induction methodology. Ultimately, two examples with some comparisons are given to verify the applicability and superior performance of the obtained results.

Aperiodic intermittent dynamic event-triggered synchronization control for stochastic delayed multi-links complex networks

In this work, the exponential synchronization issue of stochastic complex networks with time delays and time-varying multi-links (SCNTM) is discussed via a novel aperiodic intermittent dynamic event-triggered control (AIDE-TC). The AIDE-TC is designed by combining intermittent control with an exponential function and dynamic event-triggered control, aiming to minimize the number of the required triggers. Then, based on the proposed control strategy, the sufficient conditions for exponential synchronization in mean square of SCNTM are obtained by adopting graph theoretic approach and Lyapunov function method. In the meanwhile, it is proven that the Zeno behavior can be excluded under the AIDE-TC, which ensures the feasibility of the control mechanism to realize the synchronization of SCNTM. Finally, we provide a numerical simulation on islanded microgrid systems to validate the effectiveness of main results and the simulation comparison results show that the AIDE-TC can reduce the number of event triggers.

Finite-time quasi-projective synchronization of fractional-order reaction-diffusion delayed neural networks

This paper investigates the finite-time quasi-projective synchronization (FTQPS) issue of fractional-order reaction-diffusion neural networks (FORDNNs). To the best of our knowledge, this paper introduces the concept of FTQPS for the first time. First, an integral-type Lyapunov function is constructed relying on the characterization of the reaction-diffusion term and some inequality methods. Subsequently, the nonlinear feedback control strategy is designed to achieve the FTQPS goal and some sufficient conditions are obtained to guarantee FTQPS of FORDNNs. Further, the system's synchronization speed is measured by estimating the settling time. It should be noted that the above control strategy is also applicable to conventional integer-order reaction-diffusion neural networks with time delays. Finally, a numerical example is used to illustrate the validity of the theoretical analysis presented.

Complete synchronization of discrete-time variable-order fractional neural networks with time delays

This paper investigates complete synchronization of discrete-time variable-order fractional neural networks (DVFNNs) with time delays. By discrete inequality technologies and nabla Laplace transform, two stability lemmas are derived which are generalizations of the constant-order case. Furthermore, several complete synchronization criteria for DVFNNs are proposed by utilizing inequality techniques and Lyapunov method. Finally, a numerical example is provided to verify the theoretical results. This paper also provides a stability analysis method for variable-order fractional discrete-time systems.

Navigating the Metaverse: A Comprehensive Analysis of Consumer Electronics Prospects and Challenges

Rapid innovation in consumer electronics has made our lives more comfortable. Consumer electronics serve as the primary platform for the Metaverse (MV), offering users an immersive and interactive medium that connects the digital and real worlds. Consumer electronics play a crucial role in ensuring the accessibility and the user experience within the Metaverse. Despite the vital role of consumer electronics in enabling an immersive metaverse experience, a detailed survey has yet to cover different facets. Addressing this research gap, we present a comprehensive review covering several applications, case studies, and challenges of consumer electronics in Metaverse. We present the role and scope of different consumer electronics devices like VR(Virtual Reality) headsets, AR(Augmented Reality) headsets, haptic feedback devices, and smartphones in Metaverse applications. We present an illustrative case study on how consumer electronics assist education in the Metaverse. Several device-specific challenges include restricted field of view, latency issues, synchronization issues, and non-device-specific challenges like interoperability, scalability, and data privacy. Our survey shall help researchers explore more prospects for making this integration stronger.

Fixed-time stability analysis of general impulsive systems and application to synchronization of complex networks with hybrid impulses

In this paper, the fixed-time stability of general impulsive systems and the fixed-time synchronization issue of impulsive complex networks are investigated. First, the fixed-time stability of a class of nonlinear systems with general impulsive effects is analyzed by means of inequality method and using some special functions. Then, the developed fixed-time stability results are used to study the fixed-time synchronization of impulsive complex networks under the saturation controller. Compared with some early published works, in this paper, the estimation accuracy of settling time is improved by calculating the value of improper integral more precisely, and the saturation controller effectively suppresses chattering phenomenon caused by discontinuous signum function. Lastly, some numerical examples are given to verify the feasibility of our theoretical results.

Finite/fixed-time cluster synchronization for directed and multiplex coupled dynamic networks

This article deals with finite/fixed-time cluster synchronization (FnTCS/FdTCS) issue for directed and multiplex coupled dynamic networks (MCDNs). Finite/fixed-time synchronization of multiplex networks has become a popular research topic, which indicates that, state information is utilized for synchronization, and the settling time depends on original condition for a range of finite time, while the time is bounded with arbitrary original value for fixed-time one. Through constructing appropriate feedback control protocol, FnTCS and FdTCS matters for MCDNs are settled under re-arranging variables' order technique. The present model contains the case that outer matrices (OMs) can be directed, with competitive elements, and not even connected, while previous and related researches assumed that OMs were undirected, cooperative and connected, so existing results can be improved for more general and broader regulations. This strategy above is presented to solve directed CDNs with multiweights from angle of inner and outer matrices, and we prove that if the weighted group of added OMs for each dimension is strongly connected, then cluster synchronization rules are established in finite/fixed time. Moreover, we also earn finite/fixed-time synchronization criteria when the cluster is single. In addition, the issue of FnTCS/FdTCS is developed for directed and multiplex coupled reaction-diffusion networks (MCRDNs) as an application. The validity of these gained results is verified by simulated examples.

SYNCHRONIZATION PROBLEMS OF SIMULTANEOUS TRANSLATION

Among the many difficulties encountered in simultaneous interpreting - an important feature of multilingual communication in various international contexts - synchronization issues stand out. This article analyzes many synchronization problems and the nature of synchronization problems, their causes, effects, and potential solutions. We highlight the technological, environmental, and cognitive components that create these challenges. We will also discuss modern strategies and methods to reduce the difficulties and problems during synchronization, while improving the accuracy and efficiency of simultaneous interpretation.

Digital Twin-Enhanced Adaptive Traffic Signal Framework under Limited Synchronization Conditions

Unmanned traffic signal control is regarded as a sustainable intelligent management methodology. However, it faces the challenge of unpredictable traffic flow due to stochastic arrivals. The digital twin (DT) has emerged as a promising approach to address the challenges of time-varying traffic demand in urban transportation. Previous studies of DT-based adaptive traffic signal control (ATSC) methods all assume ideal synchronization conditions between the DT and the physical twin (PT). It means that the DT can immediately figure out the next neglecting limitation of realistic conditions, i.e., discrepancies between the DT and PT and computational ability. This paper proposes a DT-ATSC framework aimed at reducing the total delay at isolated intersections under limited synchronization conditions. The framework contains two parts: (1) a cell transmission model-based intersection simulation model featuring less computational consumption and the parameter self-calibration mechanism; and (2) scheme searching algorithms that can guide the DT to create optimization-oriented signal timing scheme candidates. Three options are provided for the scheme searching algorithms, i.e., grid search (GS), the genetic algorithm (GA), and Bayesian optimization (BO). A testing platform is created to validate the effectiveness of the proposed DT-ATSC. Experimental results indicate that the proposed DT-ATSC-BO outperforms the DT-ATSC-GA and DT-ATSC-GS. Meanwhile, the average vehicle delay of the DT-ATSC-BO is up to 53% lower than that of the current adaptive signal control method, which indicates that the proposed DT-ATSC has achieved the expected effect. Moreover, compared to the previous related work, the proposed DT-ATSC framework is more likely to be able to be applied in realistic situations because synchronization issues are incorporated in the design of the DT-ATSC by assuming a limited margin time for a decision.

Fixed/Prescribed-time synchronization of multi-layer complex networks under switching control

The fixed/preassigned time (FT/PT) synchronization issue of multi-layer networks via a discontinuous control strategy is addressed in this paper. Firstly, the inventiveness FT theorem is established, and a precise estimation of setting time is given by employing mathematical induction, proof by contradiction, and maximum value theory. Subsequently, based on the FT stability results, several FT synchronization criteria for multi-layer networks are proposed by designing a periodically switching protocol. Additionally, the topological connectivity constraints are eliminated through the implementation of synchronized states as virtual nodes. Correspondingly, the PT synchronization issue is investigated by developing several extraordinary control strategies in which the control gains are finite. Ultimately, the feasibility of the developed control design and the established criteria is illustrated by two numerical examples.

Design and Construction of a Portable IoT Station.

This paper discusses the design and implementation of a portable IoT station. Communication and data synchronization issues in several installations are addressed here, making possible a detailed analysis of the entire system during its operation. The system operator requires a synchronized data stream, combining multiple communication protocols into one single time stamp. The hardware selected for the portable IoT station complies with the International Electrotechnical Commission (IEC) industrial standards. A short discussion regarding interface customization shows how easily the hardware can be modified so that it is integrated with almost any system. A programmable logic controller enables the Node-RED to be utilized. This open-source middleware defines operations for each global variable nominated in the Modbus register. Two applications are presented and discussed in this paper; each application has a distinct methodology utilized to publish and visualize the acquired data. The portable IoT station is highly customizable, consisting of a modular structure and providing the best platform for future research and development of dedicated algorithms. This paper also demonstrates how the portable IoT station can be implemented in systems where time-based data synchronization is essential while introducing a seamless implementation and operation.

Secure impulsive cluster synchronization control of complex dynamical networks with parameter mismatches under deception attacks

The issue of secure cluster synchronization (SCS) of complex dynamical networks (CDNs) with parameter mismatches under deception attacks is investigated in this article. Firstly, the deception attacks are supposed to inject false information into controller-to-actuator channels, while the occurrences of deception attack are always subject to Bernoulli distribution. Secondly, an improved pinning impulsive control strategy is designed. The impulsive gain in the control strategy is take from a new range. Moreover, we obtain the estimation of synchronization error upper bound and boundaries of secure synchronization region. The synchronization error will converge to a bounded ball that depends on attack energy at a exponential rate. The CDNs without deception attacks under pinning impulsive control can achieve complete cluster synchronization. Finally, two numerical examples with 20 nodes based on MATLAB software are presented to demonstrate the effectiveness of the theoretical results.

Finite-time synchronization criteria on delayed FOCVNNs with uncertain parameters and difference operator

This article analyzes the finite-time synchronization (FTS) issues of delayed complex-valued neural networks (CVNNs) with uncertain parameters and fractional difference operator. Firstly, a significant lemma is derived based on discrete fractional calculus. The proposed lemma can help us reach FTS and estimate the setting time. Next, two controllers with delay terms are established, respectively. The designed control strategies can effectively remove delay terms. By utilizing the proposed lemma, control strategies and inequality techniques, the conditions for FTS are derived. The setting time has also been estimated. Finally, we present two examples to demonstrate the theoretical results.