Cascaded ELM-Based Joint Frame Synchronization and Channel Estimation over Rician Fading Channel with Hardware Imperfections

Due to the interdependency of frame synchronization(FS)and channel estimation(CE),joint FS and CE(JFSCE)schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems.Although traditional JFSCE schemes alleviate the influence between FS and CE,they show deficiencies in dealing with hardware imperfection(HI)and deterministic line-of-sight(LOS)path.To tackle this challenge,we proposed a cascaded ELM-based JFSCE to alleviate the influence of HI in the scenario of the Rician fading channel.Specifically,the conventional JFSCE method is first employed to extract the initial features,and thus forms the non-Neural Network(NN)solutions for FS and CE,respectively.Then,the ELMbased networks,named FS-NET and CE-NET,are cascaded to capture the NN solutions of FS and CE.Simulation and analysis results show that,compared with the conventional JFSCE methods,the proposed cascaded ELM-based JFSCE significantly reduces the error probability of FS and the normalized mean square error(NMSE)of CE,even against the impacts of parameter variations.

Dynamics and synchronization of neural models with memristive membranes under energy coupling

Dynamical modeling of neural systems plays an important role in explaining and predicting some features of biophysical mechanisms.The electrophysiological environment inside and outside of the nerve cell is different.Due to the continuous and periodical properties of electromagnetic fields in the cell during its operation,electronic components involving two capacitors and a memristor are effective in mimicking these physical features.In this paper,a neural circuit is reconstructed by two capacitors connected by a memristor with periodical mem-conductance.It is found that the memristive neural circuit can present abundant firing patterns without stimulus.The Hamilton energy function is deduced using the Helmholtz theorem.Further,a neuronal network consisting of memristive neurons is proposed by introducing energy coupling.The controllability and flexibility of parameters give the model the ability to describe the dynamics and synchronization behavior of the system.

Transient Damping of Virtual Synchronous Generator for Enhancing Synchronization Stability during Voltage Dips

Virtual synchronous generators(VSGs)are widely introduced to the renewable power generation,the variablespeed pumped storage units,and so on,as a promising gridforming solution.It is noted that VSGs can provide virtual inertia for frequency support,but the larger inertia would worsen the synchronization stability,referring to keeping synchronization with the grid during voltage dips.Thus,this paper presents a transient damping method of VSGs for enhancing the synchronization stability during voltage dips.It is revealed that the loss of synchronization(LOS)of VSGs always accompanies with the positive frequency deviation and the damping is the key factor to remove LOS when the equilibrium point exists.In order to enhance synchronization stability during voltage dips,the transient damping is proposed,which is generated by the frequency deviation in active power loop.Additionally,the proposed method can realize seamless switching between normal state and grid fault.Moreover,detailed control design for transient damping gain is given to ensure the synchronization stability under different inertia requirements during voltage dips.Finally,the experimental results are presented to validate the analysis and the effectiveness of the improved transient damping method.

A frequency domain estimation and compensation method for system synchronization parameters of distributed-HFSWR

To analyze the influence of time synchronization error,phase synchronization error,frequency synchronization error,internal delay of the transceiver system,and range error and angle error between the unit radars on the target detection performance,firstly,a spatial detection model of distributed high-frequency surface wave radar(distributed-HFSWR)is established in this paper.In this model,a method for accurate extraction of direct wave spectrum based on curve fitting is proposed to obtain accurate system internal delay and frequency synchronization error under complex electromagnetic environment background and low signal to noise ratio(SNR),and to compensate for the shift of range and Doppler frequency caused by time-frequency synchronization error.The direct wave component is extracted from the spectrum,the range estimation error and Doppler estimation error are reduced by the method of curve fitting,and the fitting accuracy of the parameters is improved.Then,the influence of frequency synchronization error on target range and radial Doppler velocity is quantitatively analyzed.The relationship between frequency synchronization error and radial Doppler velocity shift and range shift is given.Finally,the system synchronization parameters of the trial distributed-HFSWR are obtained by the proposed spectrum extraction method based on curve fitting,the experimental data is compensated to correct the shift of the target,and finally the correct target parameter information is obtained.Simulations and experimental results demonstrate the superiority and correctness of the proposed method,theoretical derivation and detection model proposed in this paper.

Synchronization and firing mode transition of two neurons in a bilateral auditory system driven by a high–low frequency signal

The FitzHugh–Nagumo neuron circuit integrates a piezoelectric ceramic to form a piezoelectric sensing neuron,which can capture external sound signals and simulate the auditory neuron system.Two piezoelectric sensing neurons are coupled by a parallel circuit consisting of a Josephson junction and a linear resistor,and a binaural auditory system is established.Considering the non-singleness of external sound sources,the high–low frequency signal is used as the input signal to study the firing mode transition and synchronization of this system.It is found that the angular frequency of the high–low frequency signal is a key factor in determining whether the dynamic behaviors of two coupled neurons are synchronous.When they are in synchronization at a specific angular frequency,the changes in physical parameters of the input signal and the coupling strength between them will not destroy their synchronization.In addition,the firing mode of two coupled auditory neurons in synchronization is affected by the characteristic parameters of the high–low frequency signal rather than the coupling strength.The asynchronous dynamic behavior and variations in firing modes will harm the auditory system.These findings could help determine the causes of hearing loss and devise functional assistive devices for patients.

Quantum synchronization with correlated baths

We study quantum synchronization under the nonequilibrium reservoirs.We consider a two-qubit XXZ chain coupled independently to their own reservoirs modeled by the collisional model.Two reservoir particles,initially prepared in a thermal state or a state with coherence,are correlated through a unitary transformation and afterward interact locally with the two quantum subsystems.We study the quantum effect of reservoir on synchronous dynamics of system.By preparing different reservoir initial states or manipulating the reservoir particles coupling and the temperature gradient,we find that quantum entanglement of reservoir is the key to control quantum synchronization of system qubits.

A Synchronization Acquisition Algorithm Based on the Frequency Hopping Pulses Combining

As modern electromagnetic environments are more and more complex,the anti-interference performance of the synchronization acquisition is becoming vital in wireless communications.With the rapid development of the digital signal processing technologies,some synchronization acquisition algorithms for hybrid direct-sequence(DS)/frequency hopping(FH)spread spectrum communications have been proposed.However,these algorithms do not focus on the analysis and the design of the synchronization acquisition under typical interferences.In this paper,a synchronization acquisition algorithm based on the frequency hopping pulses combining(FHPC)is proposed.Specifically,the proposed algorithm is composed of two modules:an adaptive interference suppression(IS)module and an adaptive combining decision module.The adaptive IS module mitigates the effect of the interfered samples in the time-domain or the frequencydomain,and the adaptive combining decision module can utilize each frequency hopping pulse to construct an anti-interference decision metric and generate an adaptive acquisition decision threshold to complete the acquisition.Theory and simulation demonstrate that the proposed algorithm significantly enhances the antiinterference and anti-noise performances of the synchronization acquisition for hybrid DS/FH communications.

Dynamics and synchronization in a memristor-coupled discrete heterogeneous neuron network considering noise

Research on discrete memristor-based neural networks has received much attention.However,current research mainly focuses on memristor–based discrete homogeneous neuron networks,while memristor-coupled discrete heterogeneous neuron networks are rarely reported.In this study,a new four-stable discrete locally active memristor is proposed and its nonvolatile and locally active properties are verified by its power-off plot and DC V–I diagram.Based on two-dimensional(2D)discrete Izhikevich neuron and 2D discrete Chialvo neuron,a heterogeneous discrete neuron network is constructed by using the proposed discrete memristor as a coupling synapse connecting the two heterogeneous neurons.Considering the coupling strength as the control parameter,chaotic firing,periodic firing,and hyperchaotic firing patterns are revealed.In particular,multiple coexisting firing patterns are observed,which are induced by different initial values of the memristor.Phase synchronization between the two heterogeneous neurons is discussed and it is found that they can achieve perfect synchronous at large coupling strength.Furthermore,the effect of Gaussian white noise on synchronization behaviors is also explored.We demonstrate that the presence of noise not only leads to the transition of firing patterns,but also achieves the phase synchronization between two heterogeneous neurons under low coupling strength.

Proposal for a realtime Einstein-synchronization-defined satellite virtual clock

Realization of high performance satellite onboard clock is vital for various positioning, navigation, and timing applications. For further improvement of the synchronization-based satellite time and frequency references, we propose a geosynchronous(GEO) satellite virtual clock concept based on ground–satellite synchronization and present a beacon transponder structure for its implementation(scheduled for launch in 2025), which does not require atomic clocks to be mounted on the satellite. Its high performance relies only on minor modifications to the existing transponder structure of GEO satellites. We carefully model the carrier phase link and analyze the factors causing link asymmetry within the special relativity. Considering that performance of such synchronization-based satellite clocks is primarily limited by the link's random phase noise, which cannot be adequately modeled, we design a closed-loop experiment based on commercial GEO satellites for pre-evaluation. This experiment aims at extracting the zero-means random part of the ground-satellite Ku-band carrier phase via a feedback loop. Ultimately, we obtain a 1σ value of 0.633 ps(two-way link), following the Gaussian distribution. From this result, we conclude that the proposed real-time Einstein-synchronization-defined satellite virtual clock can achieve picosecond-level replication of onboard time and frequency.

Geometric Error Identification of Gantry-Type CNC Machine Tool Based on Multi-Station Synchronization Laser Tracers

Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement.We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control(CNC)machine tools.This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method.We consider a three-axis gantry-type CNC machine tool,and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain.The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle.A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg-Marquardt nonlinear least squares method,and the geometric error is solved using Taylor’s first-order linearization iteration.The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer.For a volume of 800 mm×1000 mm×350 mm,the maximum differences of the linear,angular,and spatial position errors were 2.0μm,2.7μrad,and 12.0μm,respectively,which verifies the accuracy of the proposed algorithm.This research proposes a modeling method for the precise measurement of errors in machine tools,and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

Effects of Serum Concentration, Synchronization Time and Confluence on the Cell-Cycle Synchronization Efficiency of Goat Fibroblasts

This study aims to evaluate the effect of serum concentration, synchronization time, and confluence degree on the synchronisation efficiency of goat fibroblast cycle. The results indicated that there was no difference in the percentage of nucleated fibroblasts in the G0/G1 stage between serum concentrations of 0.3% and 0.4% (83.89% and 82.69%, respectively, P > 0.05) as well as between serum concentrations of 0.2% and 0.5% (76.95% and 75.46%, respectively, P > 0.05). The percentage of nucleated fibroblasts in the G0/G1 stage was highest at the concentration of 0.3% and lowest in the control group (83.89% vs. 62.67%, P 0.05). The beneficial effect of high confluence was confirmed by the large percentage of nucleated fibroblasts at the G0/G1 stage. The 60% confluency was significantly lower than the 80% and 100% confluency (73.44%, 86.63%, and 87.17%, respectively, P < 0.05). The results indicate that the goat fibroblast cycle synchronization is the most effective at the serum concentration of 0.3%, 72 hours of synchronization and 100% confluency.

Suppression and synchronization of chaos in uncertain time-delay physical system

The mechanical horizontal platform(MHP)system exhibits a rich chaotic behavior.The chaotic MHP system has applications in the earthquake and offshore industries.This article proposes a robust adaptive continuous control(RACC)algorithm.It investigates the control and synchronization of chaos in the uncertain MHP system with time-delay in the presence of unknown state-dependent and time-dependent disturbances.The closed-loop system contains most of the nonlinear terms that enhance the complexity of the dynamical system;it improves the efficiency of the closed-loop.The proposed RACC approach(a)accomplishes faster convergence of the perturbed state variables(synchronization errors)to the desired steady-state,(b)eradicates the effect of unknown state-dependent and time-dependent disturbances,and(c)suppresses undesirable chattering in the feedback control inputs.This paper describes a detailed closed-loop stability analysis based on the Lyapunov-Krasovskii functional theory and Lyapunov stability technique.It provides parameter adaptation laws that confirm the convergence of the uncertain parameters to some constant values.The computer simulation results endorse the theoretical findings and provide a comparative performance.

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution Power Internet of Things

Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase difference.In this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase difference.Specifically,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small timescale.Simulation shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.

Einstein’s Concept of Clock Synchronization Conflicts with the Second Relativity Postulate

Einstein defined clock synchronization whenever photon pulses with timetags traverse a fixed distance between two clocks with equal time spans ineither direction. Using the second relativity postulate, he found clocksmounted on a rod uniformly moving parallel with the rod’s length cannot besynchronized, but clocks attached to a stationary rod can. He dismissed thisdiscrepancy by claiming simultaneity and clock synchronization were not commonbetween inertial frames, but this paper proves with both Galilean and Lorentztransformations that simultaneity and clock synchronization are preservedbetween inertial frames. His derivation means moving clocks can never besynchronized in a “resting” inertial frame. Ultraprecise atomic clocks intimekeeping labs daily contradict his results. No algebraic error occurred inEinstein’s derivations. The two cases of clocksattached to a rod reveal three major conflicts with the currentsecond postulate. The net velocity between a photon source and detector plusthe “universal” velocity c is mathematically equivalent toEinstein’s clock synchronization method. As the ultraprecise timekeepingcommunity daily synchronizes atomic clocks on the moving Earth withultraprecise time uncertainty well below Einstein’s lowest limit ofsynchronization, the theoretical resolution of the apparent conflict isaccomplished by expanding the second relativity postulate to incorporate thenet velocity between the photon source and detector with the emitted velocity c as components of the total velocity c. This means the magnitudeof the total photon velocity can exceed the speed limit (299792458 m/s) set by the standard velocity c. .

Intermittent Control for Fixed-Time Synchronization of Coupled Networks

Dear Editor, This letter deals with fixed-time synchronization(Fd-TS) of complex networks(CNs) under aperiodically intermittent control(AIC)for the first time. The average control rate and a new Lyapunov function are proposed to overcome the difficulty of dealing with fixedtime stability/synchronization of CNs for AIC.

A master-slave generalized predictive synchronization control for preheating process of multi-cavity hot runner system

As a key component of injection molding,multi-cavity hot runner(MCHR)system faces the crucial problem of polymer melt filling imbalance among the cavities.The thermal imbalance in the system has been considered as the leading cause.Hence,the solution may rest with the synchronization of those heating processes in MCHR system.This paper proposes a’Master-Slave’generalized predictive synchronization control(MS-GPSC)method with’Mr.Slowest’strategy for preheating stage of MCHR system.The core of the proposed method is choosing the heating process with slowest dynamics as the’Master’to track the setpoint,while the other heating processes are treated as‘Slaves’tracking the output of’Master’.This proposed method is shown to have the good ability of temperature synchronization.The corresponding analysis is conducted on parameters tuning and stability,simulations and experiments show the strategy is effective.

FIXED/PREASSIGNED-TIME SYNCHRONIZATION OF QUATERNION-VALUED NEURAL NETWORKS INVOLVING DELAYS AND DISCONTINUOUS ACTIVATIONS: A DIRECT APPROACH

The fixed-time synchronization and preassigned-time synchronization are investigated for a class of quaternion-valued neural networks with time-varying delays and discontinuous activation functions. Unlike previous efforts that employed separation analysis and the real-valued control design, based on the quaternion-valued signum function and several related properties, a direct analytical method is proposed here and the quaternion-valued controllers are designed in order to discuss the fixed-time synchronization for the relevant quaternion-valued neural networks. In addition, the preassigned-time synchronization is investigated based on a quaternion-valued control design, where the synchronization time is preassigned and the control gains are finite. Compared with existing results, the direct method without separation developed in this article is beneficial in terms of simplifying theoretical analysis, and the proposed quaternion-valued control schemes are simpler and more effective than the traditional design, which adds four real-valued controllers. Finally, two numerical examples are given in order to support the theoretical results.

A 5M Synchronization Mechanism for Digital Twin Shop-Floor

In recent years,as a promising way to realize digital transformation,digital twin shop-floor(DTS)plays an impor-tant role in smart manufacturing.The core feature of DTS is the synchronization.How to implement and maintain the synchronization is critical for DTS.However,there is still a lack of a common definition for synchronization in DTS.Besides,a systematic synchronization mechanism for DTS is strongly needed.This paper first summarizes the defi-nition and requirements of synchronization in DTS,to clarify the understanding of synchronization in DTS.Then,a 5M synchronization mechanism for DTS is proposed,where 5M refers to multi-system data,multi-fidelity model,multi-resource state,multi-level state,and multi-stage operation.As a bottom-up synchronization mechanism,5M synchronization mechanism for DTS has the potential to support DTS to achieve and maintain physical-virtual state synchronization,and to realize operation synchronization of DTS.The implementation methods of 5M synchronization mechanism for DTS are also introduced.Finally,the proposed synchronization mechanism is validated in a digital twin satellite assembly shop-floor,which proves the effectiveness and feasibility of the mechanism.

Synchronization–desynchronization transitions in networks of circle maps with sinusoidal coupling

Coupled phase oscillators are adopted as powerful platforms in studying synchrony behaviors emerged in various systems with rhythmic dynamics. Much attention has been focused on coupled time-continuous oscillators described by differential equations. In this paper, we study the synchronization dynamics of networks of coupled circle maps as the discrete version of the Kuramoto model. Despite of its simplicity in mathematical form, it is found that discreteness may induce many interesting synchronization behaviors. Multiple synchronization and desynchronization transitions of both phases and frequencies are found with varying the coupling among circle-map oscillators. The mechanisms of these transitions are interpreted in terms of the mean-field approach, where collective bifurcation cascades are revealed for coupled circle-map oscillators.

Explosive synchronization of multi-layer complex networks based on star connection between layers with delay

Explosive synchronization(ES)is a kind of first-order jump phenomenon that exists in physical and biological systems.In recent years,researchers have focused on ES between single-layer and multi-layer networks.Most research on complex networks with delay has focused on single-layer or double-layer networks,multi-layer networks are seldom explored.In this paper,we propose a Kuramoto model of frequency weights in multi-layer complex networks with delay and star connections between layers.Through theoretical analysis and numerical verification,the factors affecting the backward critical coupling strength are analyzed.The results show that the interaction between layers and the average node degree has a direct effect on the backward critical coupling strength of each layer network.The location of the delay,the size of the delay,the number of network layers,the number of nodes,and the network topology are revealed to have no direct impact on the backward critical coupling strength of the network.Delay is introduced to explore the influence of delay and other related parameters on ES.