A Parametric Amplifier for Weak, Low-Frequency Forces

2015 ◽  
Author(s):  
Amit Dolev ◽  
Izhak Bucher
Keyword(s):  
Multiple Scales ◽  
Low Frequency ◽  
Parametric Amplifier ◽  
Noise Levels ◽  
Signal To Noise ◽  
External Excitation ◽  
Practical Applications ◽  
Analytic Expressions ◽  
Frequency Excitation ◽  
Selection Of

The present work introduces a tunable parametric amplifier (PA) with a hardening, Duffing-type nonlinearity. By introducing a multi-frequency parametric excitation, one is able to achieve both: (i) High amplification of the weak, low-frequency external excitation (ii) Projection of the low frequency on any natural frequency of the system, thus transforming the low frequency excitation to a frequency band where signal levels are considerably higher. Having developed multiple-scales based expressions for the response of such systems, it is demonstrated that (a) The analytical analysis agrees well with numerically obtained simulations. (b) Both the phase, magnitude and spatial projection of this force on any system’s eigenvector can be retrieved by appropriate selection of parameters, with superior signal to noise levels. Closed form analytic expressions for the sensitivity and gain are derived and analyzed. Additionally, some practical applications envisaged for the proposed method will be outlined.

scholarly journals A Probabilistic Model For Co-Occurrence Analysis in Bibliometrics

2021 ◽  
Author(s):  
Xiaobei Zhou ◽  
Miao Zhou ◽  
Desheng Huang ◽  
Lei Cui
Keyword(s):  
Probabilistic Model ◽  
Statistical Significance ◽  
Low Frequency ◽  
Critical Threshold ◽  
P Value ◽  
Model Framework ◽  
Practical Applications ◽  
Mesh Terms ◽  
Occurrence Matrix ◽  
Selection Of

Abstract The co-occurrence analysis of Medical Subject Heading (MeSH) terms in the bibliographic database is popularly used in bibliometrics. Practically for making the result interpretable, it is necessary to apply a certain filter procedure of co-occurrence matrix for removing the low-frequency items that should not appear in the final result due to their low representativeness for co-occurrence analysis. Unfortunately, there is rare research referring to determine a critical threshold to remove noise of data for co-occurrence analysis. Here, we propose a probabilistic model for co-occurrence analysis that can calculate statistical significance (p-values) of co-occurred items. With help of this model, the dimensionality of co-occurrence network could be conveniently reduced according to selection of different levels of p-value thresholds. The conceptual model framework, simulation and practical applications are illustrated in the manuscript. Further details (including all reproducible codes) can be downloaded from the project website: https://github.com/Miao-zhou/Co-occurrence-analysis.git.

scholarly journals Aspects of direct phasing in femtosecond nanocrystallography

2014 ◽  
Vol 369 (1647) ◽  
pp. 20130498 ◽  
Author(s):  
Rick P. Millane ◽  
Joe P. J. Chen
Keyword(s):  
Free Electron Laser ◽  
Phase Retrieval ◽  
Laser Diffraction ◽  
Intensity Data ◽  
Noise Levels ◽  
Signal To Noise ◽  
X Ray ◽  
Unit Cells ◽  
Diffraction Patterns ◽  
Selection Of

X-ray free-electron laser diffraction patterns from protein nanocrystals provide information on the diffracted amplitudes between the Bragg reflections, offering the possibility of direct phase retrieval without the use of ancillary experimental data. Proposals for implementing direct phase retrieval are reviewed. These approaches are limited by the signal-to-noise levels in the data and the presence of different and incomplete unit cells in the nanocrystals. The effects of low signal to noise can be ameliorated by appropriate selection of the intensity data samples that are used. The effects of incomplete unit cells may be small in some cases, and a unique solution is likely if there are four or fewer molecular orientations in the unit cell.

GA-Based Optimized Image Watermarking Method With Histogram and Butterworth Filtering

2021 ◽  
pp. 851-873
Author(s):  
Sunesh Malik ◽  
Rama Kishore Reddlapalli ◽  
Girdhar Gopal
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Signal To Noise Ratio ◽  
Image Watermarking ◽  
Low Frequency ◽  
Digital Image Watermarking ◽  
Signal To Noise ◽  
Significant Parameter ◽  
Frequency Components ◽  
Selection Of

The present paper proposes a new and significant method of optimization for digital image watermarking by using a combination of Genetic Algorithms (GA), Histogram and Butterworth filtering. In this proposed method, the histogram range selection of low frequency components is taken as a significant parameter which assists in bettering the imperceptibility and robustness against attacks. The tradeoff between the perceptual transparency and robustness is considered as an optimization puzzle which is solved with the help of Genetic Algorithm. As a result, the experimental outcomes of the present approach are obtained. These results are secure and robust to various attacks such as rotation, cropping, scaling, additive noise and filtering attacks. The peak signal to noise ratio (PSNR) and Normalized cross correlation (NC) are carefully analyzed and assessed for a set of images and MATLAB2016B software is employed as a means of accomplishing or achieving these experimental results.

scholarly journals Modeling and Simulation Technology of High Frequency Vibratory Stress Relief Treatment for Complex Thin -Walled Workpiece

2018 ◽  
Vol 206 ◽  
pp. 04001 ◽  
Author(s):  
Xian-yang Zhao ◽  
Nian-song Zhang ◽  
Ai-min Wang
Keyword(s):  
High Frequency ◽  
Excitation Frequency ◽  
Low Frequency ◽  
Stress Relief ◽  
Response Analysis ◽  
Finite Element Software ◽  
Frequency Excitation ◽  
Thin Walled ◽  
Harmonic Response Analysis ◽  
Selection Of

The current research based on vibratory stress relief (VSR) is focused on low frequency excitation, but it is seldom mentioned for complex thin-walled workpiece with higher natural frequency. In this paper, the mechanism of high frequency VSR is studied by microdynamic theory. Aiming at the rotating frame of complex thin-walled workpiece in aerospace equipment, the high frequency VSR numerical simulation is carried out by finite element software Abaqus, the modal analysis technology and harmonic response analysis technology are proposed, and the exciting force, excitation frequency and other important parameters are determined. The simulation results are analyzed to verify the superiority of high frequency VSR to eliminate residual stresses of complex thin-walled workpieces, and provide a theoretical basis for optimal selection of excitation parameters for high frequency VSR.

Thermal Stratification in a Pool with Submerged Heater Under Low Frequency Excitation

2021 ◽  
Author(s):  
SatendraPal Chauhan ◽  
Dinesh Kumar Chandraker ◽  
Naveen Kumar
Keyword(s):  
Thermal Stratification ◽  
Low Frequency ◽  
Heat Removal ◽  
Seismic Excitation ◽  
External Excitation ◽  
Thermal Mixing ◽  
Potential Applications ◽  
Frequency Excitation ◽  
Submergence Depth ◽  
Residual Heat

Abstract Thermal stratification has potential applications in the nuclear and solar industries. Thermal performance of passive residual heat removal systems and solar heaters is affected by the thermal stratification in a pool. Under the seismic condition, thermal stratification behavior of liquid in the pool has never been studied and reported in the literature. The present work focuses on the experimental investigation of thermal stratification in a pool under the seismic condition with the horizontally mounted heater simulating heat exchanger. Effect of heater submergence depth, frequency of excitation and amplitude of displacement on the thermal stratification has been studied. It was observed that the heater submergence depth significantly influences the thermal stratification in a pool. When a pool is subjected to an external excitation, the pool water separates into two zones; convective and impulsive. If the heater submergence depth in the impulsive zone, excitation effects are not found. If heater submergence depth is close to convective zone, significant effects are observed. However, it was observed that only first mode of excitation with large amplitude helps to achieve complete thermal mixing and higher modes of excitation have the minimal on the mitigating of thermal stratification. Non-dimensional stratification number has been evaluated to explain the mitigation of thermal stratification with seismic excitation.

scholarly journals Locating and Imaging through Scattering Medium in a Large Depth

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 90
Author(s):  
Shuo Zhu ◽  
Enlai Guo ◽  
Qianying Cui ◽  
Lianfa Bai ◽  
Jing Han ◽  
...  
Keyword(s):  
Phase Space ◽  
Signal To Noise Ratio ◽  
Speckle Pattern ◽  
Heuristic Method ◽  
Scattering Medium ◽  
Scattering Media ◽  
Signal To Noise ◽  
Practical Applications ◽  
Large Depth ◽  
Strong Scattering

Scattering medium brings great difficulties to locate and reconstruct objects especially when the objects are distributed in different positions. In this paper, a novel physics and learning-heuristic method is presented to locate and image the object through a strong scattering medium. A novel physics-informed framework, named DINet, is constructed to predict the depth and the image of the hidden object from the captured speckle pattern. With the phase-space constraint and the efficient network structure, the proposed method enables to locate the object with a depth mean error less than 0.05 mm, and image the object with an average peak signal-to-noise ratio (PSNR) above 24 dB, ranging from 350 mm to 1150 mm. The constructed DINet firstly solves the problem of quantitative locating and imaging via a single speckle pattern in a large depth. Comparing with the traditional methods, it paves the way to the practical applications requiring multi-physics through scattering media.

Does Motion Perception Follow Weber's Law?

Perception ◽  
1995 ◽  
Vol 24 (4) ◽  
pp. 363-372 ◽  
Author(s):  
Johannes M Zanker
Keyword(s):  
Motion Perception ◽  
Stimulus Intensity ◽  
Signal To Noise Ratio ◽  
Weber’S Law ◽  
Noise Levels ◽  
Signal To Noise ◽  
Weber's Law ◽  
The Absolute ◽  
Noise Ratio ◽  
Random Dot Patterns

The subjective strength of a percept often depends on the stimulus intensity in a nonlinear way. Such coding is often reflected by the observation that the just-noticeable difference between two stimulus intensities (JND) is proportional to the absolute stimulus intensity. This behaviour, which is usually referred to as Weber's Law, can be interpreted as a compressive nonlinearity extending the operating range of a sensory system. When the noise superimposed on a motion stimulus is increased along a logarithmic scale (in order to provide linear steps in subjective difference) in motion-coherency measurements, observers often report that the subjective differences between the various noise levels increase together with the absolute level. This observation could indicate a deviation from Weber's Law for variation of motion strength as obtained by changing the signal-to-noise ratio in random-dot kinematograms. Thus JNDs were measured for the superposition of uncorrelated random-dot patterns on static random-dot patterns and three types of motion stimuli realised as random-dot kinematograms, namely large-field and object ‘Fourier’ motion (all or a group of dots move coherently), ‘drift-balanced’ motion (a travelling region of static dots), and paradoxical ‘theta’ motion (the dots on the surface of an object move in opposite direction to the object itself). For all classes of stimuli, the JNDs when expressed as differences in signal-to-noise ratio turned out to increase with the signal-to-noise ratio, whereas the JNDs given as percentage of superimposed noise appear to be similar for all tested noise levels. Thus motion perception is in accordance with Weber's Law when the signal-to-noise ratio is regarded as stimulus intensity, which in turn appears to be coded in a nonlinear fashion. In general the Weber fractions are very large, indicating a poor differential sensitivity in signal-to-noise measurements.

scholarly journals Synergetic Use of Sentinel-1 and Sentinel-2 Data for Soil Moisture Mapping at Plot Scale

2018 ◽  
Vol 10 (8) ◽  
pp. 1285 ◽  
Author(s):  
Reza Attarzadeh ◽  
Jalal Amini ◽  
Claudia Notarnicola ◽  
Felix Greifeneder
Keyword(s):  
Soil Moisture ◽  
Optical Data ◽  
Estimation Accuracy ◽  
Support Vector ◽  
Practical Applications ◽  
Initial Stage ◽  
Object Based ◽  
Single Polarization ◽  
Selection Of

This paper presents an approach for retrieval of soil moisture content (SMC) by coupling single polarization C-band synthetic aperture radar (SAR) and optical data at the plot scale in vegetated areas. The study was carried out at five different sites with dominant vegetation cover located in Kenya. In the initial stage of the process, different features are extracted from single polarization mode (VV polarization) SAR and optical data. Subsequently, proper selection of the relevant features is conducted on the extracted features. An advanced state-of-the-art machine learning regression approach, the support vector regression (SVR) technique, is used to retrieve soil moisture. This paper takes a new look at soil moisture retrieval in vegetated areas considering the needs of practical applications. In this context, we tried to work at the object level instead of the pixel level. Accordingly, a group of pixels (an image object) represents the reality of the land cover at the plot scale. Three approaches, a pixel-based approach, an object-based approach, and a combination of pixel- and object-based approaches, were used to estimate soil moisture. The results show that the combined approach outperforms the other approaches in terms of estimation accuracy (4.94% and 0.89 compared to 6.41% and 0.62 in terms of root mean square error (RMSE) and R2), flexibility on retrieving the level of soil moisture, and better quality of visual representation of the SMC map.

scholarly journals Polytetrafluoroethylene Films in Rigid Polyurethane Foams’ Dielectric Permittivity Measurements with a One-Side Access Capacitive Sensor

Polymers ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1173
Author(s):  
Ilze Beverte ◽  
Ugis Cabulis ◽  
Sergejs Gaidukovs
Keyword(s):  
Dielectric Properties ◽  
Dielectric Permittivity ◽  
Low Frequency ◽  
Capacitive Sensor ◽  
Polyurethane Foams ◽  
Active Area ◽  
Ptfe Film ◽  
Practical Applications ◽  
Permittivity Measurements ◽  
The Impact

As a non-metallic composite material, widely applied in industry, rigid polyurethane (PUR) foams require knowledge of their dielectric properties. In experimental determination of PUR foams’ dielectric properties protection of one-side capacitive sensor’s active area from adverse effects caused by the PUR foams’ test objects has to be ensured. In the given study, the impact of polytetrafluoroethylene (PTFE) films, thickness 0.20 mm and 0.04 mm, in covering or simulated coating the active area of one-side access capacitive sensor’ electrodes on the experimentally determined true dielectric permittivity spectra of rigid PUR foams is estimated. Penetration depth of the low frequency excitation field into PTFE and PUR foams is determined experimentally. Experiments are made in order to evaluate the difference between measurements on single PUR foams’ samples and on complex samples “PUR foams + PTFE film” with two calibration modes. A modification factor and a small modification criterion are defined and values of modifications are estimated in numerical calculations. Conclusions about possible practical applications of PTFE films in dielectric permittivity measurements of rigid PUR foams with one-side access capacitive sensor are made.

Denoising for full-waveform inversion with expanded prediction-error filters

Geophysics ◽  
2021 ◽  
pp. 1-54
Author(s):  
Milad Bader ◽  
Robert G. Clapp ◽  
Biondo Biondi
Keyword(s):  
High Frequency ◽  
Prediction Error ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Frequency Data ◽  
Signal To Noise ◽  
Frequency Signal ◽  
Full Waveform

Low-frequency data below 5 Hz are essential to the convergence of full-waveform inversion towards a useful solution. They help build the velocity model low wavenumbers and reduce the risk of cycle-skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often field data are high-pass filtered before any processing step, sacrificing weak but essential signal for full-waveform inversion. We propose to denoise the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high signal-to-noise ratio. The constructed filter captures the multi-dimensional spectrum of the high-frequency signal. We expand the filter's axes in the time-space domain to compress its spectrum towards the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data non-stationarity while retaining the simplicity of stationary filters, we divide the data into non-overlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and non-stationary data, and we show it improves the full-waveform inversion results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates non-stationary shear energy recorded by the vertical component of ocean-bottom nodes.

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