Off-axis digital holography plays a crucial role in high-precision three-dimensional imaging. However, high-resolution phase images are often affected by the limited pixel size of the sensor. To address this issue, th...
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Sampling and communication are both crucial for coordination in multi-agent systems(MASs), with sampling capturing raw data from the environment for control decision making, and communication ensuring the data is shar...
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Sampling and communication are both crucial for coordination in multi-agent systems(MASs), with sampling capturing raw data from the environment for control decision making, and communication ensuring the data is shared effectively for synchronized and informed control decisions across agents. However, practical MASs often operate in environments where continuous and synchronous data samplings and exchanges are impractical, necessitating strategies that can handle intermittent sampling and communication constraints. This paper provides a comprehensive survey of recent advances in distributed coordination control of MASs under intermittent sampling and communication, focusing on both foundational principles and state-of-the-art techniques. After introducing fundamentals, such as communication topologies,agent dynamics, control laws, and typical coordination objectives, the distinctions between sampling and communication are elaborated, exploring deterministic versus random, synchronous versus asynchronous, and instantaneous versus sequential scenarios. A detailed review of emerging trends and techniques is then presented, covering time-triggered, event-triggered,communication-protocol-based, and denial-of-service-resilient coordination control. These techniques are analyzed across various attack models, including those based on data loss, sampled data, time constraints, and topology switching. By synthesizing these developments, this survey aims to equip researchers and practitioners with a clearer understanding of current challenges and methodologies, concluding with insights into promising future directions.
Background: The main objective of the Internet of Things (IoT) has significantly influenced and altered technology, such as interconnection, interoperability, and sensor devices. To ensure seamless healthcare faciliti...
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Task scheduling for virtual machines (VMs) has shown to be essential for the effective development of cloud computing at the lowest cost and fastest turnaround time. A number of research gaps about job schedule optimi...
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To address the privacy concerns that arise from centralizing model training on a large number of IoT devices, a revolutionary new distributed learning framework called federated learning has been developed. This setup...
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Because the aerospace-ground Internet no longer relies on deploying infrastructure such as base stations,it has the advantage of all-weather full coverage services that traditional terrestrial networks do not ***,the ...
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Because the aerospace-ground Internet no longer relies on deploying infrastructure such as base stations,it has the advantage of all-weather full coverage services that traditional terrestrial networks do not ***,the traditional global navigation satellite system does not support communication *** newly developing aerospace network system is still in the construction stage,and there is no applicable solution *** communication technology is an important method to solve the contradiction between the low battery capacity of the Internet of things(IoT)node and the high energy consumption of *** is the development trend of the ***,the current passive technology based on Wi-Fi and other signals cannot achieve arbitrary communication due to the excitation signal acquisition *** solve the above two major problems,this paper proposes a passive system design for aerospace-ground IoT *** system can use the global navigation signal as excitation signal for backscatter *** the global navigation signal has the characteristics of all-weather and full coverage,this design solves the carrier acquisition problem in previous *** addition,this paper also proposes a low-power signal detection technology that can detect navigation signals with high precision on passive *** evaluate system performance through simulation *** experimental results show that the backscatter system based on global navigation satellite signals can realize efficient communication of IoT nodes.
Designing efficient and durable hydrogen evolution reaction（HER） catalysts for seawater electrolysis is crucial for large-scale hydrogen ***,we introduce a theory-driven design of metal/WN electrocatalysts,with meta...
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Designing efficient and durable hydrogen evolution reaction（HER） catalysts for seawater electrolysis is crucial for large-scale hydrogen ***,we introduce a theory-driven design of metal/WN electrocatalysts,with metal strongly coupled to lattice-matched *** calculations for Pt/WN reveal that W sites enhance H2O adsorption/dissociation,optimizing Pt's H *** prepared Pt/WN@CP nanorods can catalyze HER with low overpotentials of 107 and 113 mV at 500 mA cm-2in alkaline water/seawater,respectively,surpassing Pt/*** calculations and experiments show that the optimized Ni/WN@CP-90 achieves an optimal ΔGH*and overpotential of 219 mV at 500 mA cm-2in alkaline seawater,demonstrating the versatility of the WN support to promote HER ***,the anion exchange membrane water electrolyzer（AEMWE） constructed by Pt/WN@CP or Ni/WN@CP-90 with NiFe-LDH@NF demonstrates outstanding hydrogen production activity with excellent Faraday efficiency（～100%） and durability（120 h）,indicating the potential application of WN-supported catalysts for efficient and stable seawater electrolysis.
Federated Class-Incremental Learning (FCIL) aims to design privacy-preserving collaborative training methods to continuously learn new classes from distributed datasets. In these scenarios, federated clients face the ...
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Dear Editor,This letter presents a new transfer learning framework for the deep multi-agent reinforcement learning(DMARL) to reduce the convergence difficulty and training time when applying DMARL to a new scenario [1...
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Dear Editor,This letter presents a new transfer learning framework for the deep multi-agent reinforcement learning(DMARL) to reduce the convergence difficulty and training time when applying DMARL to a new scenario [1], [2].
Inspired by basic circuit connection methods,memristors can also be utilized in the construction of complex discrete chaotic *** investigate the dynamical effects of hybrid memristors,we propose two hybrid tri-memrist...
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Inspired by basic circuit connection methods,memristors can also be utilized in the construction of complex discrete chaotic *** investigate the dynamical effects of hybrid memristors,we propose two hybrid tri-memristor hyperchaotic(HTMH)mapping structures based on the hybrid parallel/cascade and cascade/parallel operations,*** the HTMH mapping structure with hybrid parallel/cascade operation as an example,this map possesses a spatial invariant set whose stability is closely related to the initial states of the *** distributions and bifurcation behaviours dependent on the control parameters are explored with numerical ***,the memristor initial offset-boosting mechanism is theoretically demonstrated,and memristor initial offset-boosting behaviours are numerically *** results clarify that the HTMH map can exhibit hyperchaotic behaviours and extreme multistability with homogeneous coexisting infinite *** addition,an FPGA hardware platform is fabricated to implement the HTMH map and generate pseudorandom numbers(PRNs)with high ***,the generated PRNs can be applied in Wasserstein generative adversarial nets(WGANs)to enhance training stability and generation capability.
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