Research of Adaptive Gradient Projection Algorithm on Remote Sensing Image Reconstruction

2013 ◽  
Vol 765-767 ◽  
pp. 572-575 ◽  
Author(s):  
Hai Xia Yan ◽  
Yan Jun Liu
Keyword(s):  
Remote Sensing ◽  
Image Reconstruction ◽  
High Frequency ◽  
Remote Sensing Image ◽  
Gradient Projection ◽  
Projection Algorithm ◽  
Frequency Noise ◽  
Noise Effect ◽  
High Frequency Noise ◽  
Projection Direction

In order to improve the low efficient and the noise effect of remote sensing image reconstruction, an algorithm of adaptive dual gradient projection for sparse reconstruction of compressed sensing theory is proposed. Point to the high frequency noise of remote sensing image, the ADGPSR algorithm pursuits the projection direction in two conjudate directions, thus the high frequency noise effect is overcame. Experiment results show that, compared with the GPSR algorithm, the ADGPSR algorithm on remote sensing image improves the signals reconstruction accuracy.

Case study: Simulation and control of high frequency noise for commercial vehicle cab considering leak

2019 ◽  
Vol 67 (4) ◽  
pp. 315-329
Author(s):  
Rongjiang Tang ◽  
Zhe Tong ◽  
Weiguang Zheng ◽  
Shenfang Li ◽  
Li Huang
Keyword(s):  
High Frequency ◽  
Commercial Vehicle ◽  
Frequency Noise ◽  
High Frequency Noise ◽  
Simulation And Control ◽  
And Control

Aerodynamic noise from an asymmetric airfoil with perforated extension plates at the trailing edge

2020 ◽  
pp. 1475472X2097838
Author(s):  
CK Sumesh ◽  
TJS Jothi
Keyword(s):  
High Frequency ◽  
Sound Pressure ◽  
Pore Diameter ◽  
Low Frequency ◽  
Aerodynamic Noise ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Trailing Edge ◽  
High Frequency Noise ◽  
Displacement Thickness

This paper investigates the noise emissions from NACA 6412 asymmetric airfoil with different perforated extension plates at the trailing edge. The length of the extension plate is 10 mm, and the pore diameters ( D) considered for the study are in the range of 0.689 to 1.665 mm. The experiments are carried out in the flow velocity ( U∞) range of 20 to 45 m/s, and geometric angles of attack ( αg) values of −10° to +10°. Perforated extensions have an overwhelming response in reducing the low frequency noise (<1.5 kHz), and a reduction of up to 6 dB is observed with an increase in the pore diameter. Contrastingly, the higher frequency noise (>4 kHz) is observed to increase with an increase in the pore diameter. The dominant reduction in the low frequency noise for perforated model airfoils is within the Strouhal number (based on the displacement thickness) of 0.11. The overall sound pressure levels of perforated model airfoils are observed to reduce by a maximum of 2 dB compared to the base airfoil. Finally, by varying the geometric angle of attack from −10° to +10°, the lower frequency noise is seen to increase, while the high frequency noise is observed to decrease.

Bayesian deconvolution of gamma‐ray logs

Geophysics ◽  
1987 ◽  
Vol 52 (11) ◽  
pp. 1535-1546 ◽  
Author(s):  
Ping Sheng ◽  
Benjamin White ◽  
Balan Nair ◽  
Sandra Kerford
Keyword(s):  
High Frequency ◽  
Gamma Ray ◽  
Simulated Data ◽  
Field Measurements ◽  
Bayesian Optimization ◽  
Frequency Noise ◽  
High Frequency Noise ◽  
Data Application ◽  
Gamma Ray Detector ◽  
Gamma Ray Log

The spatial resolution of gamma‐ray logs is defined by the length 𝓁 of the gamma‐ray detector. To resolve thin beds whose thickness is less than 𝓁, it is generally desirable to deconvolve the data to reduce the averaging effect of the detector. However, inherent in the deconvolution operation is an amplification of high‐frequency noise, which can be a detriment to the intended goal of increased resolution. We propose a Bayesian statistical approach to gamma‐ray log deconvolution which is based on optimization of a probability function which takes into account the statistics of gamma‐ray log measurements as well as the empirical information derived from the data. Application of this method to simulated data and to field measurements shows that it is effective in suppressing high‐frequency noise encountered in the deconvolution of gamma‐ray logs. In particular, a comparison with the least‐squares deconvolution approach indicates that the incorporation of physical and statistical information in the Bayesian optimization process results in optimal filtering of the deconvolved results.

High frequency noise of MOSFETs. II. Experiments

1998 ◽  
Vol 42 (11) ◽  
pp. 2083-2092 ◽  
Author(s):  
C.H. Chen ◽  
M.J. Deen ◽  
Z.X. Yan ◽  
M. Schroter ◽  
C Enz
Keyword(s):  
High Frequency ◽  
Frequency Noise ◽  
High Frequency Noise
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