High Frequency Resolution Research Articles

Advanced Frequency Analysis of Signals with High-Frequency Resolution

In today’s era, it is important to analyze and utilize various signals in industrial or laboratory applications. Measured signals provide critical information about the controlled system, which can be contained precisely within a narrow frequency range. Many methods and algorithms exist to process such signals in both the time and frequency domains. In particular, signal processing in the frequency domain is primary in industrial practice because dominant components within a specific narrow frequency band are sought. The discrete Fourier transformation (DFT) algorithm is the tool used in practice to find these frequency components. The DFT algorithm provides the full frequency spectrum with a higher number of calculation steps, and its spectrum frequency resolution is low. Therefore, research has focused on finding a method to achieve high-frequency spectrum resolution. An important factor in selecting the technique was that such an algorithm should be implementable on a microprocessor-based system under harsh industrial conditions. Research results showed that the DFT ZOOM method meets these requirements. The frequency zoom has many advantages but requires some modification. It is implemented in high-performance analyzers, but a thorough and detailed description of the respective algorithm is lacking in technical articles and literature. This article mathematically and theoretically describes the modified frequency zoom algorithm in detail. The steps of the frequency zoom, from creating an analytical signal through frequency shifting and decimation to the frequency analysis of the signal, are realized. The algorithm allows for the analysis of a signal with high-frequency resolution in a limited frequency band. A significant modification of DFT ZOOM is that of using the Hilbert transform to create an analytic signal. This resolves the aliasing issue caused by the overlap between fundamental and sideband spectra. Results from processing deterministic and stochastic signals using the modified DFT ZOOM are presented. The presented experimental results contribute to a more detailed frequency analysis of the signal. As part of this scientific research, the issues of frequency zoom were thoroughly addressed, solving the partial problems of this algorithm, both in theory and in the context of signal theory.

Automatic High-Resolution Operational Modal Identification of Thin-Walled Structures Supported by High-Frequency Optical Dynamic Measurements.

High-frequency optical dynamic measurement can realize multiple measurement points covering the whole surface of the thin-walled structure, which is very useful for obtaining high-resolution spatial information for damage localization. However, the noise and low calculation efficiency seriously hinder its application to real-time, online structural health monitoring. To this end, this paper proposes a novel high-resolution frequency domain decomposition (HRFDD) modal identification method, combining an optical system with an accelerometer for measuring high-accuracy vibration response and introducing a clustering algorithm for automated identification to improve efficiency. The experiments on the cantilever aluminum plate were carried out to evaluate the effectiveness of the proposed approach. Natural frequency and damping ratios were obtained by the least-squares complex frequency domain (LSCF) method to process the acceleration responses; the high-resolution mode shapes were acquired by the singular value decomposition (SVD) processing of global displacement data collected by high-speed cameras. Finally, the complete set of the first nine order modal parameters for the plate within the frequency range of 0 to 500 Hz has been determined, which is closely consistent with the results obtained from both experimental modal analysis and finite element analysis; the modal parameters could be automatically picked up by the DBSCAN algorithm. It provides an effective method for applying optical dynamic technology to real-time, online structural health monitoring, especially for obtaining high-resolution mode shapes.

Fine frequency structure of interstellar scintillation pattern in radio emission of the PSR B1133+16 at 111 MHz

The B1133+16 pulsar was observed at a frequency of 111 MHz with the LPA PRAO radio telescope from October 2022 to March 2023. Observations were made twice a week for two days in a row. In total 38 measurements of the scattering parameters were carried out with a high frequency resolution (up to 65 Hz). We used continuous recording of voltage in the frequency band 2.5 MHz with 8-bit digitization. The signal was reconstructed using the coherent dedispersion method. Dynamic spectra (DSP) were constructed for each observing session. Then, for each DSP, we calculated a two-dimensional autocorrelation function (2DACF) and analyzed its frequency and time sections. We have studied the fine frequency structure of pulsar scintillations by analyzing both the dynamic spectra, and the spectra of individual pulses. It has been found that the intrinsic shape of diffraction distortion on average can be represented by a sharp two-sided function with a characteristic frequency width of 1–2 kHz. The long-term variability of the following parameters has been carefully studied: characteristic scales in frequency and time (fdifandtdif), and rotation measureRM. Based on the analysis of long-term variations, it is suggested that the true frequency form of scintillations may be distorted by ionospheric effects. We also compared the scintillation parameters separately for the two mean profile components, and no differences between the parameters were found.

Improving the frequency resolution of distribution of relaxation times by integrating elastic net regularization and quantum particle swarm optimization

The distribution of relaxation times (DRT) method is an efficient approach for analyzing electrochemical impedance spectroscopy (EIS) of fuel cells. However, facing electrochemical processes with close characteristic times/frequencies, low frequency resolution of DRT puts a damper on the analysis of results. To address this problem, a new DRT method integrating elastic net regularization and quantum particle swarm optimization (QPSO) algorithm is proposed in this study. Elastic net regularization combines the advantages of Lasso's feature selection and Tikhonov's coefficient shrinkage, thereby enhancing the frequency resolution of DRT. The use of the QPSO algorithm avoids the manual selection of parameters. A comprehensive evaluation of the developed method is conducted using both synthetic EIS and experimental EIS. The results show that the developed DRT method shows good performance and the reconstructed DRT functions exhibit high frequency resolution and accuracy. Overall, the proposed DRT method holds promise for advancing the characterization of fuel cells.

The Power of Precision: High-Resolution Backscatter Frequency Drift in RFID Identification

The Power of Precision: High-Resolution Backscatter Frequency Drift in RFID Identification

Frequency-hopping along with resolution-turning for fast and enhanced reconstruction in ultrasound tomography

The distorted Born iterative (DBI) method is considered to obtain images with high-contrast and resolution. Besides satisfying the Born approximation condition, the frequency-hopping (FH) technique is necessary to gradually update the sound contrast from the first iteration and progress to the actual sound contrast of the imaged object in subsequent iterations. Inspired by the fact that the higher the frequency, the higher the resolution. Because low-frequency allows for low-resolution object imaging, hence for high-resolution imaging requirements, using low-frequency to possess a high-resolution image from the first iteration will be less efficient. For an effective reconstruction, the object’s resolution at low frequencies should be small. And similarly, with high frequencies, the object resolution should be larger. Therefore, in this paper, the FH, and the resolution-turning (RT) technique are proposed to obtain object images with high-contrast and -resolution. The convergence speed in the initial iterations is rapidly achieved by utilizing low frequency in the frequency-turning technique and low image resolution in the resolution-turning technique. It is crucial to ensure accurate object reconstruction for subsequent iterations. The desired spatial resolution is attained by employing high frequency and large image resolution. The resolution-turning distorted Born iterative (RT-DBI) and frequency-hopping distorted Born iterative (FH-DBI) solutions are thoroughly investigated to exploit their best performance. This makes sense because if it is not good to choose the number of iterations for the frequency f1 in FH-DBI and for the resolution of N1 × N1 in RT-DBI, then these solutions give even worse quality than traditional DBI. After that, the RT-FH-DBI integration was investigated in two sub-solutions. We found that the lower frequency f1 used both before and after the RT would get the best performance. Consequently, compared to the traditional DBI approaches, the normalized error and total runtime for the reconstruction process were dramatically decreased, at 83.6% and 18.6%, respectively. Besides fast and quality imaging, the proposed solution RT-FH-DBI is promised to produce high-contrast and high-resolution object images, aiming at object reconstruction at the biological tissue. The development of 3D imaging and experimental verification will be studied further.

Photocurrent interference spectroscopy of solids and characterization of semiconductor solar-cell materials

Photocurrent measurements are widely used to study the intrinsic optoelectronic properties of semiconductors, such as photocarrier generation efficiency and carrier mobility, as well as evaluate the performance of optoelectronic devices, such as solar cells and photodetectors. Interferometric spectroscopy precisely measures optical properties and gathers optical spectra information on semiconductors. Consequently, photocurrent-based interferometric measurements, with high signal-to-noise ratios, high resolution, and broad frequency bandwidths, can probe the energy distributions of low-density defects and impurities and investigate charge transport in materials and devices. Here, we demonstrate that photocurrent interference spectroscopy reveals the intrinsic properties of solar-cell materials: bulk crystals of GaAs and halide perovskite, and thin films of halide perovskite and quantum dot. We show that homodyne interference spectroscopy of photocurrent can monitor low-density localized states in semiconductors and that it can be used in combination with other spectroscopy techniques, such as photoluminescence measurements, to provide a deep understanding of photocurrent generation processes. Furthermore, we show that heterodyne interference spectroscopy of photocurrent can be used to investigate the frequency dependence of material parameters, such as the dielectric constant, absorption coefficient, and reflectance. As an application, we used interference spectroscopy of photocurrent to show the impact of multiexcitons on the photoabsorption and photocarrier generation processes in quantum dot solar cells. Finally, we used it to reveal the distinctive spectral characteristics at the band edge of a halide perovskite, which is considered to be an exceptional solar-cell material with high energy conversion efficiency.

Johnson-noise-limited cancellation-free microwave impedance microscopy with monolithic silicon cantilever probes

Microwave impedance microscopy (MIM) is an emerging scanning probe technique for nanoscale complex permittivity mapping and has made significant impacts in diverse fields. To date, the most significant hurdles that limit its widespread use are the requirements of specialized microwave probes and high-precision cancellation circuits. Here, we show that forgoing both elements not only is feasible but also enhances performance. Using monolithic silicon cantilever probes and a cancellation-free architecture, we demonstrate Johnson-noise-limited, drift-free MIM operation with 15 nm spatial resolution, minimal topography crosstalk, and an unprecedented sensitivity of 0.26 zF/√Hz. We accomplish this by taking advantage of the high mechanical resonant frequency and spatial resolution of silicon probes, the inherent common-mode phase noise rejection of self-referenced homodyne detection, and the exceptional stability of the streamlined architecture. Our approach makes MIM drastically more accessible and paves the way for advanced operation modes as well as integration with complementary techniques.

Temporal resolution relates to sensory hyperreactivity independently of stimulus detection sensitivity in individuals with autism spectrum disorder.

Researchers have been focusing on perceptual characteristics of autism spectrum disorder (ASD) in terms of sensory hyperreactivity. Previously, we demonstrated that temporal resolution, which is the accuracy to differentiate the order of two successive vibrotactile stimuli, is associated with the severity of sensory hyperreactivity. We currently examined whether an increase in the perceptual intensity of a tactile stimulus, despite its short duration, is derived from high temporal resolution and high frequency of sensory temporal summation. Twenty ASD and 22 typically developing (TD) participants conducted two psychophysical experimental tasks to evaluate detectable duration of vibrotactile stimulus with same amplitude and to evaluate temporal resolution. The sensory hyperreactivity was estimated using self-reported questionnaire. There was no relationship between the temporal resolution and the duration of detectable stimuli in both groups. However, the ASD group showed severe sensory hyperreactivity in daily life than TD group, and the ASD participants with severe sensory hyperreactivity tended to have high temporal resolution, not high sensitivity of detectable duration. Contrary to the hypothesis, there might be different processing between temporal resolution and sensitivity for stimulus detection. We suggested that the atypical temporal processing would affect to sensory reactivity in ASD.

The ALMA-QUARKS Survey. II. The ACA 1.3 mm Continuum Source Catalog and the Assembly of Dense Gas in Massive Star-Forming Clumps

Leveraging the high resolution, sensitivity, and wide frequency coverage of the Atacama Large Millimeter/submillimeter Array (ALMA), the QUARKS survey, standing for “Querying Underlying mechanisms of massive star formation with ALMA-Resolved gas Kinematics and Structures”, is observing 139 massive star-forming clumps at ALMA Band 6 (λ ∼ 1.3 mm). This paper introduces the Atacama Compact Array (ACA) 7 m data of the QUARKS survey, describing the ACA observations and data reduction. Combining multi-wavelength data, we provide the first edition of QUARKS atlas, offering insights into the multiscale and multiphase interstellar medium in high-mass star formation. The ACA 1.3 mm catalog includes 207 continuum sources that are called ACA sources. Their gas kinetic temperatures are estimated using three formaldehyde transitions with a non-LTE radiation transfer model, and the mass and density are derived from a dust emission model. The ACA sources are massive (16–84 percentile values of 6–160 M ⊙), gravity-dominated (M ∝ R 1.1) fragments within massive clumps, with supersonic turbulence ( M>1 ) and embedded star-forming protoclusters. We find a linear correlation between the masses of the fragments and the massive clumps, with a ratio of 6% between the two. When considering fragments as representative of dense gas, the ratio indicates a dense gas fraction (DGF) of 6%, although with a wide scatter ranging from 1% to 10%. If we consider the QUARKS massive clumps to be what is observed at various scales, then the size-independent DGF indicates a self-similar fragmentation or collapsing mode in protocluster formation. With the ACA data over four orders of magnitude of luminosity-to-mass ratio (L/M), we find that the DGF increases significantly with L/M, which indicates clump evolutionary stage. We observed a limited fragmentation at the subclump scale, which can be explained by a dynamic global collapse process.

High-resolution frequency domain decomposition for modal analysis of bridges using train-induced free-vibrations

Modal parameters are structural inherent characteristics that can be applied for revealing performance of railway bridges. Free vibration signals generated by a passage of train are commonly utilized to estimate the modal parameters of railway bridges due to their higher signal-to-noise ratios compared to random vibrations caused by ambient loads. However, since free vibration signals rapidly decay over time, the available free-vibration data is typically short-time. When using the fast Fourier transform-based spectral estimation method for modal identification from short-time vibration data, a phenomenon known as spectral leakage occurs, leading to miss-identification of some structural modes. In this study, the classical frequency domain decomposition (FDD) is improved for modal identification of railway bridges, in which the higher resolution auto-power spectral density (PSD) and cross-PSD functions are calculated through the autoregressive (AR) model-based method. The AR model-based method improves both the smoothness and resolution of the PSD functions compared to the fast Fourier transform technique. These AR model-based PSD functions are then employed in the FDD process to facilitate frequency and mode shape identification while avoiding spurious noise modes. The proposed eigenvalue fitting technique is subsequently utilized to estimate damping ratios. Numerical simulation data as well as vibration data from an actual bridge are analyzed to validate the proposed method, with a comparison made to the Welch’s PSD-based method. The results demonstrate that the modified FDD approach enables more effective identification of structural modes, even in the presence of closely-spaced modes.

Cooltools: Enabling high-resolution Hi-C analysis in Python.

Chromosome conformation capture (3C) technologies reveal the incredible complexity of genome organization. Maps of increasing size, depth, and resolution are now used to probe genome architecture across cell states, types, and organisms. Larger datasets add challenges at each step of computational analysis, from storage and memory constraints to researchers' time; however, analysis tools that meet these increased resource demands have not kept pace. Furthermore, existing tools offer limited support for customizing analysis for specific use cases or new biology. Here we introduce cooltools (https://github.com/open2c/cooltools), a suite of computational tools that enables flexible, scalable, and reproducible analysis of high-resolution contact frequency data. Cooltools leverages the widely-adopted cooler format which handles storage and access for high-resolution datasets. Cooltools provides a paired command line interface (CLI) and Python application programming interface (API), which respectively facilitate workflows on high-performance computing clusters and in interactive analysis environments. In short, cooltools enables the effective use of the latest and largest genome folding datasets.

A patterned vibrotactile method using envelope modulation with high resolution and low perceptual frequency

The virtual haptics is a crucial aspect of immersive virtual reality, extending the traditional experiences of sight and hearing. The vibration can provide direct normal vibration and friction reduction, making it a promising method to realize virtual haptics. However, the optimum perceptual threshold of skin for vibration is 100 Hz to 500 Hz, resulting in a too low vibrotactile resolution. The conflict between the low perceptual frequency and high resolution still remains challenges. In this paper, a low-frequency envelope wave methodology is proposed to realize the localized vibrotactile feedback. The high-frequency components are modulated into a low-frequency envelope waveform, which provides low-frequency perception and high resolution at the same time. Due to hardware limitations, the modes must be truncated and minimized as much as possible. This requirement conflicts with achieving localized vibration at arbitrary points and further implementing complex vibration patterns. Therefore, a modal optimization algorithm is proposed to solve the inverse problem. The modal participation coefficients is obtained, basing on the evaluation index that ensures the frequency of the envelope wave and the vibration pattern quality. The localized vibration patterns including multiple points, points of proportional amplitude, bar and circle are achieved with a resolution of 3 cm and a perception frequency of about 200 Hz. This method is expected to be applied to virtual reality, blind assistance, and other potential applications to enhance tactile interaction experiences.

Unraveling the characteristics of Parkinson's Disease through neuroimaging: Insights and future directions

Parkinson's disease (PD) is a neurodegenerative disease with a high degree of patient heterogeneity, and as of 2016 there are approximately 6.1 million PD patients worldwide. PD has a high proportion of patients with intermediate to advanced disease and a high rate of disability, and clinical diagnosis and treatment are difficult due to the lack of neuromarkers to identify disease states and the inability to quantify the effects of treatment in PD. In recent years, many researchers have explored specific changes in brain activity in PD based on electrophysiological and neuroimaging data. Electroencephalography, with its high temporal resolution and rich frequency domain information, and functional magnetic resonance imaging, with its high spatial resolution, have become the main tools to characterize the state of brain activity in PD in recent years. This paper analyses some of the available data on the characteristics of PD through two neuroimaging techniques commonly used in the disease. It concludes with the prospect of being able to establish uniform criteria for determining PD.

Seismic data AVO analysis in time frequency domain using synchroextracting transform

Time-frequency analysis is a crucial tool for processing and interpreting seismic data in hydrocarbon exploration. Accurately determining the temporal and spectral characteristics is essential for applications such as reservoir characterization and fluid identification. High-resolution representation of seismic data time-frequency properties improves reliability in these applications. Recent advancements in post-processing techniques aim to enhance conventional methods. The synchroextracting transform (SET) is an innovative approach that combines a post-processing procedure with the short-time Fourier transform. It retains time-frequency information associated with spectral components while eliminating excessive energy dispersed in the time-frequency domain. This study evaluates the effectiveness of SET for seismic data time-frequency analysis, comparing it with contemporary post-processing techniques using synthetic signals and field seismic data. Results show that SET provides higher resolution for distinct signal components and effectively reduces energy dispersion. SET exhibits advantages such as robustness against random noise, reasonable computational cost, and offering more interpretable time-frequency information regarding attenuated amplitudes. Building on synthetic experiments, we demonstrate the capability of SET to generate high-resolution single frequency sections of seismic data, facilitating accurate analysis of amplitude variation with offset (AVO) in the time-frequency domain.

Accurate estimation of modulation amplitude in Brillouin optical correlation-domain reflectometry based on Rayleigh noise spectrum

In Brillouin optical correlation-domain reflectometry (BOCDR), spatial resolution relies on the modulation amplitude of the light. We propose a Rayleigh-based method that utilizes the spectral width of Rayleigh-induced noise to measure this amplitude without altering the setup or requiring an optical spectrum analyzer. With high frequency resolution and ease of implementation, our approach enhances the convenience and accuracy of spatial resolution evaluation in BOCDR.

High resolution frequency shift measurement based on the time domain mode-locked optoelectronic oscillator

High resolution frequency shift measurement based on the time domain mode-locked optoelectronic oscillator

Две методики измерения aмплитудно-частотных характеристик многолучевых ионосферных коротковолновых радиолиний по данным наклонного радиозондирования ионосферы

Two methods of measuring the amplitude-frequency characteristics of multipath ionospheric shortwave radio channels with high frequency resolution (tens-hundreds of hertz) are presented. Since traditional narrow-band channels do not allow to separate the various modes of ionospheric propagation of short waves interfering with each other, it is proposed in this paper to use broadband signals, which makes it possible to separate the received modes of ionospheric propagation of a radio signal, as well as to distinguish the signal from interference. The advantage of the first technique is that, together with the amplitude-frequency characteristic of the radio line, as a result, the mode pattern of multipath propagation of short waves becomes known, which allows us to draw qualitative conclusions about the propagation of radio waves, as well as to apply classifications according to empirical multipath models. Disadvantages of the first technique: the manual stage of the selection of mode tracks on the ionograms of oblique sensing, as well as the loss of some information about the energy of the mode tracks due to the diffuseness (blurring) of the traces of mode tracks on the ionogram. The second method, on the contrary, gives only an estimate of the amplitude-frequency characteristics of a multipath shortwave radio line without revealing the mode pattern of multipath, but does it automatically and without losing information about the energy of diffuse tracks. The presentation of both methods in one article allows you to indicate the advantages and disadvantages of each of them, and, accordingly, the preferred areas of application. Since it is important to have a set of techniques with an integrated system approach to the study and measurement of the characteristics of the ionosphere and ionospheric radio channels.

A maturational frequency discrimination deficit may explain developmental language disorder.

Auditory perceptual deficits are widely observed among children with developmental language disorder (DLD). Yet, the nature of these deficits and the extent to which they explain speech and language problems remain controversial. In this study, we hypothesize that disruption to the maturation of the basilar membrane may impede the optimization of the auditory pathway from brainstem to cortex, curtailing high-resolution frequency sensitivity and the efficient spectral decomposition and encoding of natural speech. A series of computational simulations involving deep convolutional neural networks that were trained to encode, recognize, and retrieve naturalistic speech are presented to demonstrate the strength of this account. These neural networks were built on top of biologically truthful inner ear models developed to model human cochlea function, which-in the key innovation of the present study-were scheduled to mature at different rates over time. Delaying cochlea maturation qualitatively replicated the linguistic behavior and neurophysiology of individuals with language learning difficulties in a number of ways, resulting in (a) delayed language acquisition profiles, (b) lower spoken word recognition accuracy, (c) word finding and retrieval difficulties, (d) "fuzzy" and intersecting speech encodings and signatures of immature neural optimization, and (e) emergent working memory and attentional deficits. These simulations illustrate many negative cascading effects that a primary maturational frequency discrimination deficit may have on early language development and generate precise and testable hypotheses for future research into the nature and cost of auditory processing deficits in children with language learning difficulties. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Frequency-comb-linearized, widely tunable lasers for coherent ranging

Tunable lasers, with the ability to continuously vary their emission wavelengths, have found widespread applications across various fields such as biomedical imaging, coherent ranging, optical communications, and spectroscopy. In these applications, a wide chirp range is advantageous for large spectral coverage and high frequency resolution. Besides, the frequency accuracy and precision also depend critically on the chirp linearity of the laser. While extensive efforts have been made on the development of many kinds of frequency-agile, widely tunable, narrow-linewidth lasers, wideband yet precise methods to characterize and linearize laser chirp dynamics are also demanded. Here we present an approach to characterize laser chirp dynamics using an optical frequency comb. The instantaneous laser frequency is tracked over terahertz bandwidth at 1 MHz intervals. Using this approach we calibrate the chirp performance of 12 tunable lasers from Toptica, Santec, New Focus, EXFO, and NKT that are commonly used in fiber optics and integrated photonics. In addition, with acquired knowledge of laser chirp dynamics, we demonstrate a simple frequency-linearization scheme that enables coherent ranging without any optical or electronic linearization unit. Our approach not only presents novel wideband, high-resolution laser spectroscopy, but is also critical for sensing applications with ever-increasing requirements on performance.