Spatial correlations in time and frequency domains between chlorophyll-a concentration and environmental factors in the Bohai Sea

Based on the reconstructed MODIS data and ECMWF reanalysis data from 2003 to 2021,spatial correlations between chlorophyll a(Chl a)and sea surface temperature(SST),photosynthetically available radiation(PAR),aerosol optical thickness(AOT),and wind speed(WS)in the Bohai Sea were analyzed from the perspective of time domain and frequency domain.Results indicate that the frequency domain analysis was more conducive to revealing the correlations between Chl a and environmental factors.The spatial pattern of time-domain correlations was similar to the isobaths of the Bohai Sea,which was positive in shallow waters and negative in deep waters for SST,PAR,and AOT,and was reversed for WS.Frequency-domain correlations were obtained by performing Fourier Transform and were higher than correlations in time domain.The spatial distributions indicated that the effects of SST and PAR on Chl a were greater than AOT and WS in the Bohai Sea.Additionally,cross-spectrum analysis was applied to explore the response relationships.A depth-dependent pattern was shown in correlations and time lags,indicating that the influential mechanism of environmental factors on Chl-a concentration is related to seawater depth.

Equalization Reconstruction Algorithm Based on Reference Signal Frequency Domain Block Joint for DTMB-Based Passive Radar

Channel equalization plays a pivotal role within the reconstruction phase of passive radar reference signals.In the context of reconstructing digital terrestrial multimedia broadcasting(DTMB)signals for low-slow-small(LSS)target detection,a novel frequency domain block joint equalization algorithm is presented in this article.From the DTMB signal frame structure and channel multipath transmission characteristics,this article adopts a unconventional approach where the delay and frame structure of each DTMB signal frame are reconfigured to create a circular convolution block,facilitating concurrent fast Fourier transform(FFT)calculations.Following equalization,an inverse fast Fourier transform(IFFT)-based joint output and subsequent data reordering are executed to finalize the equalization process for the DTMB signal.Simulation and measured data confirm that this algorithm outperforms conventional techniques by reducing signal errors rate and enhancing real-time processing.In passive radar LSS detection,it effectively suppresses multipath and noise through frequency domain equalization,reducing false alarms and improving the capabilities of weak target detection.

Exploring the asymmetric effect of COVID‑19 pandemic news on the cryptocurrency market:evidence from nonlinear autoregressive distributed lag approach and frequency domain causality

This paper explores the asymmetric effect of COVID-19 pandemic news,as measured by the coronavirus indices(Panic,Hype,Fake News,Sentiment,Infodemic,and Media Coverage),on the cryptocurrency market.Using daily data from January 2020 to September 2021 and the exponential generalized autoregressive conditional heter-oskedasticity model,the results revealed that both adverse and optimistic news had the same effect on Bitcoin returns,indicating fear of missing out behavior does not prevail.Furthermore,when the nonlinear autoregressive distributed lag model is esti-mated,both positive and negative shocks in pandemic indices promote Bitcoin’s daily changes;thus,Bitcoin is resistant to the SARS-CoV-2 pandemic crisis and may serve as a hedge during market turmoil.The analysis of frequency domain causality supports a unidirectional causality running from the Coronavirus Fake News Index and Sentiment Index to Bitcoin returns,whereas daily fluctuations in the Bitcoin price Granger affect the Coronavirus Panic Index and the Hype Index.These findings may have significant policy implications for investors and governments because they highlight the impor-tance of news during turbulent times.The empirical results indicate that pandemic news could significantly influence Bitcoin’s price.

New cooperative frequency domain differential modulation and demodulation

An innovative method of cooperative frequency domain differential modulation and demodulation is presented.This method applies the prior knowledge of channel propagation to selecting the variable differential length and carrying out frequency domain modulation.This strategy optimizes the design of system parameters to effectively improve the anti-interference ability of the differential system in time-varied multipath channel circumstance without making the execution more complicating.The simulations and comparisons demonstrate the proposed method is effective,and the results show that it is especially suitable for the fading channel with strong propagation and fast time-variation.

An Improved Frequency Domain Technique for Determining Soil Water Content

For many years a soil water content sensor with low cost, reliability and sufficient accuracy has been desirable. Thus, an improved measurement method based on the frequency domain (FD) principle for determining soil water content was considered. Unlike other measurement principles, a new measurable index, η, which was independent of the output impedance and the amplitude of the oscillator while relying on the electrical impedance of a multi-pin probe, was pro- posed. Moreover, a model for processing the impedance of the multi-pin soil probe was developed, and several important electrical parameters for establishing their operating ranges applicable to this probe were evaluated. In order to confirm the theoretical analysis, an experiment was conducted with a 4-pin probe. Using the developed model, the relationship between the proposed index η and soil volumetric water content was shown to be linear (R2 = 0.9921). Thus, as the measurable index, η seemed satisfactory.

Application of pseudo-random frequency domain electromagnetic method in mining areas with strong interferences

Due to the strong electromagnetic interferences and human interference,traditional electromagnetic methods cannot obtain high quality resistivity data of mineral deposits in Chinese mines.The wide field electromagnetic method(WFEM),in which the pseudo-random signal is taken as the transmitter source,can extract high quality resistivity data in areas with sever interference by only measuring the electric field component.We use the WFEM to extract the resistivity information of the Dongguashan mine in southeast China.Compared with the audio magnetotelluric(AMT)method,and the controlled source audio-frequency magnetotelluric(CSAMT) method,the WFEM can obtain data with higher quality and simpler operations.The inversion results indicate that the WFEM can accurately identify the location of the main ore-body,which can be used for deep mine exploration in areas with strong interference.

Sampled-Data Asynchronous Fuzzy Output Feedback Control for Active Suspension Systems in Restricted Frequency Domain

This paper proposes a novel sampled-data asynchronous fuzzy output feedback control approach for active suspension systems in restricted frequency domain.In order to better investigate uncertain suspension dynamics,the sampleddata Takagi-Sugeno(T-S)fuzzy half-car active suspension(HCAS)system is considered,which is further modelled as a continuous system with an input delay.Firstly,considering that the fuzzy system and the fuzzy controller cannot share the identical premises due to the existence of input delay,a reconstructed method is employed to synchronize the time scales of membership functions between the fuzzy controller and the fuzzy system.Secondly,since external disturbances often belong to a restricted frequency range,a finite frequency control criterion is presented for control synthesis to reduce conservatism.Thirdly,given a full information of state variables is hardly available in practical suspension systems,a two-stage method is proposed to calculate the static output feedback control gains.Moreover,an iterative algorithm is proposed to compute the optimum solution.Finally,numerical simulations verify the effectiveness of the proposed controllers.

Joint AVO inversion in the time and frequency domain with Bayesian interference

Amplitude variations with offset or incident angle （AVO/AVA） inversion are typically combined with statistical methods, such as Bayesian inference or deterministic inversion. We propose a joint elastic inversion method in the time and frequency domain based on Bayesian inversion theory to improve the resolution of the estimated P- and S-wave velocities and density. We initially construct the objective function using Bayesian inference by combining seismic data in the time and frequency domain. We use Cauchy and Gaussian probability distribution density functions to obtain the prior information for the model parameters and the likelihood function, respectively. We estimate the elastic parameters by solving the initial objective function with added model constraints to improve the inversion robustness. The results of the synthetic data suggest that the frequency spectra of the estimated parameters are wider than those obtained with conventional elastic inversion in the time domain. In addition, the proposed inversion approach offers stronger antinoising compared to the inversion approach in the frequency domain. Furthermore, results from synthetic examples with added Gaussian noise demonstrate the robustness of the proposed approach. From the real data, we infer that more model parameter details can be reproduced with the proposed joint elastic inversion.

An improved Gaussian frequency domain sparse inversion method based on compressed sensing

The traditional compressed sensing method for improving resolution is realized in the frequency domain.This method is aff ected by noise,which limits the signal-to-noise ratio and resolution,resulting in poor inversion.To solve this problem,we improved the objective function that extends the frequency domain to the Gaussian frequency domain having denoising and smoothing characteristics.Moreover,the reconstruction of the sparse refl ection coeffi cient is implemented by the mixed L1_L2 norm algorithm,which converts the L0 norm problem into an L1 norm problem.Additionally,a fast threshold iterative algorithm is introduced to speed up convergence and the conjugate gradient algorithm is used to achieve debiasing for eliminating the threshold constraint and amplitude error.The model test indicates that the proposed method is superior to the conventional OMP and BPDN methods.It not only has better denoising and smoothing eff ects but also improves the recognition accuracy of thin interbeds.The actual data application also shows that the new method can eff ectively expand the seismic frequency band and improve seismic data resolution,so the method is conducive to the identifi cation of thin interbeds for beach-bar sand reservoirs.

Sub-synchronous frequency domain-equivalent modeling for wind farms based on rotor equivalent resistance characteristics

The equivalent simplification of large wind farms is essential for evaluating the safety of power systems.However,sub-synchronous oscillations can significantly affect the stability of power systems.Although detailed mathematical models of wind farms can help accurately analyze the oscillation mechanism,the solution process is complicated and may lead to problems such as the“dimensional disaster.”Therefore,this paper proposes a sub-synchronous frequency domain-equivalent modeling method for wind farms based on the nature of the equivalent resistance of the rotor,in order to analyze sub-synchronous oscillations accurately.To this end,Matlab/Simulink is used to simulate a detailed model,a single-unit model,and an equivalent model,considering a wind farm as an example.A simulation analysis is then performed under the sub-synchronous frequency to prove that the model is effective and that the wind farm equivalence model method is valid.

A Bregman adaptive sparse-spike deconvolution method in the frequency domain

To improve the anti-noise performance of the time-domain Bregman iterative algorithm,an adaptive frequency-domain Bregman sparse-spike deconvolution algorithm is proposed.By solving the Bregman algorithm in the frequency domain,the influence of Gaussian as well as outlier noise on the convergence of the algorithm is effectively avoided.In other words,the proposed algorithm avoids data noise effects by implementing the calculations in the frequency domain.Moreover,the computational efficiency is greatly improved compared with the conventional method.Generalized cross validation is introduced in the solving process to optimize the regularization parameter and thus the algorithm is equipped with strong self-adaptation.Different theoretical models are built and solved using the algorithms in both time and frequency domains.Finally,the proposed and the conventional methods are both used to process actual seismic data.The comparison of the results confirms the superiority of the proposed algorithm due to its noise resistance and self-adaptation capability.

Decoupling coefficients of dilatational wave for Biot's dynamic equation and its Green's functions in frequency domain

Green＇s functions for Blot＇s dynamic equation in the frequency domain can be a highly useful tool for the investigation of dynamic responses of a saturated porous medium. Its applications are found in soil dynamics, seismology, earthquake engineering, rock mechanics, geophysics, and acoustics. However, the mathematical work for deriving it can be daunting. Green＇s functions have been presented utilizing an analogy between the dynamic thermoelasticity and the dynamic poroelasticity in the frequency domain using the u-p formulation. In this work, a special term ＂decoupling coefficient＂ for the decomposition of the fast and slow dilatational waves is proposed and expressed to present a new methodology for deriving the poroelastodynamic Green＇s functions. The correct- ness of the solution is demonstrated by numerically comparing the current solution with Cheng＇s previous solution. The separation of the two waves in the present methodology allows the more accurate evaluation of Green＇s functions, particularly the solution of the slow dilatational wave. This can be advantageous for the numerical implementation of the boundary element method （BEM） and other applications.

A refined Frequency Domain Decomposition tool for structural modal monitoring in earthquake engineering

Output-only structural identification is developed by a refined Frequency Domain Decomposition（rFDD） approach, towards assessing current modal properties of heavy-damped buildings（in terms of identification challenge）, under strong ground motions. Structural responses from earthquake excitations are taken as input signals for the identification algorithm. A new dedicated computational procedure, based on coupled Chebyshev Type Ⅱ bandpass filters, is outlined for the effective estimation of natural frequencies, mode shapes and modal damping ratios. The identification technique is also coupled with a Gabor Wavelet Transform, resulting in an effective and self-contained time-frequency analysis framework. Simulated response signals generated by shear-type frames（with variable structural features） are used as a necessary validation condition. In this context use is made of a complete set of seismic records taken from the FEMA P695 database, i.e. all 44 ＂Far-Field＂（22 NS, 22 WE） earthquake signals. The modal estimates are statistically compared to their target values, proving the accuracy of the developed algorithm in providing prompt and accurate estimates of all current strong ground motion modal parameters. At this stage, such analysis tool may be employed for convenient application in the realm of Earthquake Engineering, towards potential Structural Health Monitoring and damage detection purposes.

Frequency domain polarization weighted ESPRIT method for bearing angle

The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information.

DOA estimation method for wideband signals by sparse recovery in frequency domain

The traditional super-resolution direction finding methods based on sparse recovery need to divide the estimation space into several discrete angle grids, which will bring the final result some error. To this problem, a novel method for wideband signals by sparse recovery in the frequency domain is proposed. The optimization functions are found and solved by the received data at every frequency, on this basis, the sparse support set is obtained, then the direction of arrival (DOA) is acquired by integrating the information of all frequency bins, and the initial signal can also be recovered. This method avoids the error caused by sparse recovery methods based on grid division, and the degree of freedom is also expanded by array transformation, especially it has a preferable performance under the circumstances of a small number of snapshots and a low signal to noise ratio (SNR).

A Priority-aware Frequency Domain Polling MAC Protocol for OFDMA-based Networks in Cyber-physical Systems

Wireless networking in cyber-physical systems (CPSs) is characteristically different from traditional wireless systems due to the harsh radio frequency environment and applications that impose high real-time and reliability constraints. One of the fundamental considerations for enabling CPS networks is the medium access control protocol. To this end, this paper proposes a novel priority-aware frequency domain polling medium access control (MAC) protocol, which takes advantage of an orthogonal frequency-division multiple access (OFDMA) physical layer to achieve instantaneous priority-aware polling. Based on the polling result, the proposed work then optimizes the resource allocation of the OFDMA network to further improve the data reliability. Due to the non-polynomial-complete nature of the OFDMA resource allocation, we propose two heuristic rules, based on which an efficient solution algorithm to the OFDMA resource allocation problem is designed. Simulation results show that the reliability performance of CPS networks is significantly improved because of this work. © 2014 Chinese Association of Automation.

Prediction study of hydrocarbon reservoir based on time-frequency domain electromagnetic technique taking Ili Basin as an example

The time-frequency domain electromagnetic(TFEM)sounding technique can directly detect oil and gas characteristics through anomalies in resistivity and polarizability.In recent years,it has made some breakthroughs in hydrocarbon detection.TFEM was applied to predict the petroliferous property of the Ili Basin.In accordance with the geological structure characteristics of the study area,a two-dimensional layered medium model was constructed and forward modeling was performed.We used the forward-modeling results to guide fi eld construction and ensure the quality of the fi eld data collection.We used the model inversion results to identify and distinguish the resolution of the geoelectric information and provide a reliable basis for data processing.On the basis of our results,key technologies such as 2D resistivity tomography imaging inversion and polarimetric constrained inversion were developed,and we obtained abundant geological and geophysical information.The characteristics of the TFEM anomalies of the hydrocarbon reservoirs in the Ili Basin were summarized through an analysis of the electrical logging data in the study area.Moreover,the oil-gas properties of the Permian and Triassic layers were predicted,and the next favorable exploration targets were optimized.

Investigation of optical reflectance from different animal vertebra along the fixation trajectory of pedicle screw in frequency domain

Accurate placement of pedicle screw(PS)is crucial in spinal surgery.Developing new real-time intra-operative monitoring and navigation methods is an important direction of clinical appli-cation research.In this paper,we studied the spectrum along the fixation trajectory of PS in frequency domain to tackle the accuracy problem.Fresh porcine vertebrae,bovine vertebrae and ovine vertebrae were measured with the near-infrared spectrum(NIR)device to obtain the reflected spectrum from the vertebrae.Along the fixation trajectory of PS,average energy from different groups was calculated and used for identifying different tissues and compared to achieve the optimal recognition factor.Compared with the time domain approach,the frequency domain method could divide the spectra measured at different tissue points into different groups more stably and accurately,which could serve as a new method to assist the PS insertion.The results gained from this study are significant to the development of hi-tech medical instruments with independent intellectual property rights.

Nonlinearity-Compensation-Free Optical Frequency Domain Reflectometry Based on Electrically-Controlled Optical Frequency Sweep

A nonlinearity-compensation-free optical frequency domain reflectometry(OFDR)scheme is proposed and experimentally demonstrated based on the electrically-controlled optical frequency sweep.In the proposed scheme,the linear frequency sweep light is generated by propagating an ultra-narrow-linewidth continuous-wave(CW)light through an electro-optic frequency shifter which consists of a dual-parallel Mach-Zehnder modulator(DPMZM)and an electronic 90°hybrid,where the electro-optic frequency shifter is driven by a linear frequency modulated signal generated by a direct digital synthesizer(DDS).Experimental results show that the spatial resolution and signal-to-noise ratio(SNR)of the proposed OFDR scheme without the nonlinear phase compensation are comparable to those of OFDR employing a commercial tunable laser source(TLS),an auxiliary interferometer,and a software-based nonlinear phase compensation method.The proposed OFDR scheme is helpful to reduce the complexity of the optical structure and eliminate the difficulty of developing the nonlinear phase compensation algorithm.

Line of sight waypoint guidance for a container ship based on frequency domain identification of Nomoto model of vessel

CIFER software is used to identify steering and roll dynamics of a container ship. In this software, advanced features such as the Chirp-Z transform(CZT) and composite window optimization are applied to the time history of steering and roll dynamics to extract high quality frequency responses. From the extracted frequency responses, two linear transfer functions of Nomoto model are fitted for yaw and roll dynamics of the vessel. Based on the identified Nomoto model, a PID heading controller and a Kalman filter observer are constructed. The simulation results of heading controller for line of sight(LOS) waypoint guidance show excellent tracking of pilot inputs in the presence of wave induced motions and forces.