Adaptive Multi-frequency Research Articles

Domain adaptive multi-frequency underwater image enhancement network

Domain adaptive multi-frequency underwater image enhancement network

High-Speed Train Impedance Measurement Approach Based on Adaptive Multifrequency Voltage Disturbance

High-Speed Train Impedance Measurement Approach Based on Adaptive Multifrequency Voltage Disturbance

ADMNet: An adaptive downsampling multi-frequency multi-channel network for long-term time series forecasting

Long-term time series forecasting finds widespread applications in various domains such as energy, finance, and transportation. Decomposing time series into sub-sequences with distinct temporal relationships (periods) for analysis and modeling is an effective approach for long-term time series prediction. However, conventional decomposition techniques often rely on fixed-size parameter kernels for sliding averages, leading to inaccurate and unreasonable captures of the underlying periodicities in the time series. Additionally, it is essential to acknowledge that time series data often exhibits multi-periodic characteristics. In many time series prediction tasks, the value at a future time point is influenced by multiple periods within the time series. To accurately and flexibly capture the periodicities of time series, we propose an enhanced adaptive cyclic feature recognizer to automatically identify the periodic lengths for sliding average parameter kernel sizing. To fully exploit the multiple periodicities inherent in time series, we merge and smooth the sequences of features corresponding to the identified cycles, obtaining two frequency-blended cyclic feature fusion terms. Furthermore, we extract high-frequency random components to preserve finer details. Finally, we individually model the three cyclic feature fusion terms. In summary, we introduce the Adaptive Multi-Frequency Multi-Channel Network (ADMNet) designed to autonomously capture multi-periodic features. Experimental results show that, compared to the current state-of-the-art seven benchmark models, the proposed model achieves an average reduction in mean squared error (MSE) ranging from 6.19% to 22.75% across eight datasets, including ETT, Traffic, and Weather. This indicates that our model delivers superior predictive performance on multiple real-world datasets.

Adaptive Multifrequency Attribute Analysis and Its Application on Reservoir Characterization

Adaptive Multifrequency Attribute Analysis and Its Application on Reservoir Characterization

A Method for Suppressing Mass Imbalance Vibration of Magnetically Suspended Rotor-Based on Multifrequency Adaptive Estimation

Aiming at the problem that the unbalanced vibration of a high-speed magnetically suspended rotor affects the attitude angular velocity measurement accuracy of magnetically suspended control and sensitive gyroscope (MSCSG), a multifrequency vibration suppression method based on adaptive multifrequency estimation (AMFE) is proposed. First, the reason of rotor mass unbalance vibration is analyzed, the dynamic model of MSCSG with unbalance vibration is established, and its influence on spacecraft attitude angular velocity measurement accuracy is pointed out. The multifrequency vibration suppression controller and the compensation module of residual synchronous displacement stiffness force are designed when the rotor speed is unknown. The measurement signal of the radial <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${X}$ </tex-math></inline-formula> -channel displacement sensor and its orthogonal signal are used to realize the estimation of the rotor speed. Finally, the convergence of the AMFE algorithm and the stability of the system are analyzed. The simulation and experimental results show that the proposed method can effectively suppress harmonic currents and residual synchronous displacement stiffness disturbance force caused by mass imbalance. The method proposed in this article can effectively improve the attitude angular velocity measurement accuracy of MSCSG.

Experimental Assessment of a Novel Hybrid Scheme for Quantitative GPR Imaging

A hybrid inversion procedure for subsoil prospecting by ground-penetrating radar (GPR) measurements is proposed and experimentally validated in this letter. The approach integrates the benefits of qualitative beamforming in an adaptive multifrequency (MF) inexact-Newton scheme formulated in Lebesgue spaces with variable exponents. After a first preprocessing step aimed at estimating the incident field, a delay-and-sum (DAS) method provides an initial image of the region of interest. Then, the inexact-Newton algorithm exploits the qualitative indicator for both setting the exponent function and selectively weighting the update of the unknown during iterations. The proposed approach is tested against experimental GPR data.

Non‐coherent adaptive detection in passive radar exploiting polarimetric and frequency diversity

The joint exploitation of polarimetric and frequency diversity is considered in this study as a way to improve the target detection capability in a FM radio-based passive radar. The authors resort to a generalised likelihood ratio test approach and derive a fully adaptive multi-frequency polarimetric detector that optimally combines the signals simultaneously transmitted by a given illuminator of opportunity and received at different carrier frequencies by differently polarised surveillance antennas. The application of the proposed detection scheme to recorded live data demonstrates the effectiveness of the multi-frequency polarimetric operation in typical scenarios, besides the expected improvement due to non-coherent integration of target echoes received on multiple channels. In particular, it is shown to provide remarkable target discrimination capability against interfering sources as well as increased robustness with respect to the time-varying characteristics of the exploited signals of opportunity.

Adaptive multifrequency light collection by self-ordered mobile scatterers in optical resonators

Photons carry momentum, and thus their scattering not only modifies light propagation but at the same time induces forces on particles. Confining mobile scatterers and light in a closed volume thus generates a complex coupled nonlinear dynamics. As a striking example, one finds a phase transition from random order to a crystalline structure if particles within a resonator are illuminated by a sufficiently strong laser. This phase transition can be simply understood as a minimization of the optical potential energy of the particles in concurrence with a maximization of light scattering into the resonator. Here, we generalize the self-ordering dynamics to several illumination colors and cavity modes. In this enlarged model, particles adapt dynamically to current illumination conditions to ensure maximal simultaneous scattering of all frequencies into the resonator as a sort of self-optimizing light collection system with built-in memory. Such adaptive self-ordering dynamics in optical resonators could be implemented in a wide range of systems from cold atoms and molecules to mobile nanoparticles in solution. In the quantum regime, it enables exploration of uncharted regions of multiparticle phases, allowing simulation of Hopfield networks, associative memories, or generalized Hamiltonian mean field models.

Application of adaptive multi-frequency grids to three-dimensional astrophysical radiative transfer

We present a method to solve the three-dimensional (3D) radiative transfer equation for astrophysical applications using adaptive photon transport grids. Contrary to earlier treatments, they are calculated for each frequency separately. Generated minimizing the first-order discretization error in the scattered radiation intensity, they provide global error control for solutions of radiative transfer problems on the grid. We discuss minimization of the grid point number in regions where the optical depth becomes large and show that the method allows for treating applications with optical depth of any value using the concept of penetration depth. The proposed grid generation algorithm is easy to implement, allows pre-calculation of the grids and storage in integer arrays, making a fast solution of the 3D radiative transfer equation possible. The grid generation algorithm is suitable for optimization in cases where simple radiation source distributions are given. Besides discussing application to simple density distribution commonly occurring in astrophysical objects, we illustrate the capabilities of the method by generating grids for an accretion disk around a young star.

Characterisation of objects and general ocean phenomena by use of target adaptive multi-frequency multistatic matched illumination acoustics

Through modelling and detailed experimental investigations there exists in most cases a considerable amount of a priori information about the target and the background scene. Some of the signatures are very dominant and specific in nature, and some are less so and may overlap signatures related to other targets or background clutter. The authors investigate phenomena of interest in the maximum number of signature domains and present the basic matched illumination sonar concept. Subsequently they illustrate a set of specific application areas with emphasis on classification of submerged objects and their wakes against a background of gravity waves, internal waves and turbulence. Some experimental results displaying the capability of the technique are presented.

Adaptive multifrequency modulation method for an advanced laser range finder

The intensity of a laser beam is modulated with radio frequencies (RF), in a laser range finder. The modulated laser beam is directed to a target, and the reflected light is detected. The phase of the RP signal from the detector is measured. A semitransparent obstacle between the laser and the target degrades the accuracy of the range measurement. In this paper, an adaptive multifrequency modulation method is proposed and experimentally verified to overcome this problem.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An Algorithm for an Adaptive Multifrequency Receiver

This paper presents a simple and effective algorithm for an adaptive multifrequency receiver that can be used for several types of multifrequency signals. This algorithm uses the ability of frequency detection of signal processing using extreme and zero-crossing points in the multifrequency signals and an adaptive second-order notch filter.