scholarly journals Natural variability and anthropogenic effects in a Central Mediterranean core

2012 ◽  
Vol 8 (2) ◽  
pp. 831-839 ◽  
Author(s):  
S. Alessio ◽  
G. Vivaldo ◽  
C. Taricco ◽  
M. Ghil
Keyword(s):  
Isotopic Ratio ◽  
Forecast Error ◽  
Singular Spectrum Analysis ◽  
Low Frequency ◽  
Natural Variability ◽  
Central Mediterranean ◽  
Spectral Content ◽  
Frequency Components ◽  
Oxygen Isotopic ◽  
Complete Series

Abstract. We evaluate the contribution of natural variability to the modern decrease in foraminiferal δ18O by relying on a 2200-yr-long, high-resolution record of oxygen isotopic ratio from a Central Mediterranean sediment core. Pre-industrial values are used to train and test two sets of algorithms that are able to forecast the natural variability in δ18O over the last 150 yr. These algorithms are based on autoregressive models and neural networks, respectively; they are applied separately to each of the δ18O series' significant variability components, rather than to the complete series. The separate components are extracted by singular-spectrum analysis and have narrow-band spectral content, which reduces the forecast error. By comparing the sum of the predicted low-frequency components to its actual values during the Industrial Era, we deduce that the natural contribution to these components of the modern δ18O variation decreased gradually, until it reached roughly 40%, as early as the end of the 1970s.

scholarly journals Natural variability and anthropogenic effects in a Central Mediterranean core

2011 ◽  
Vol 7 (5) ◽  
pp. 3699-3718
Author(s):  
S. Alessio ◽  
G. Vivaldo ◽  
C. Taricco ◽  
M. Ghil
Keyword(s):  
Narrow Band ◽  
Isotopic Ratio ◽  
Forecast Error ◽  
Singular Spectrum Analysis ◽  
Natural Variability ◽  
Anthropogenic Effects ◽  
Central Mediterranean ◽  
Spectral Content ◽  
Oxygen Isotopic ◽  
Complete Series

Abstract. We evaluate the contribution of natural variability to the modern decrease in foraminiferal δ18O by relying on a 2200-years-long, high-resolution record of oxygen isotopic ratio from a Central Mediterranean sediment core. Pre-industrial values are used to train and test two sets of algorithms that are able to forecast the natural variability in δ18O over the last 150 yr. These algorithms are based on autoregressive models and neural networks, respectively; they are applied separately to each of the δ18O series' significant variability components, rather than to the complete series. The separate components are extracted by singular-spectrum analysis and have narrow-band spectral content, which reduces the forecast error. By comparing the sum of the predicted components to the actual values during the Industrial Era, we deduce that the natural contribution to the modern δ18O variation decreased gradually, until it reached roughly 40% as early as the end of the 1970s.

Self-sustained low-frequency components in an impinging shear layer

1982 ◽  
Vol 116 ◽  
pp. 157-186 ◽  
Author(s):  
C. Knisely ◽  
D. Rockwell
Keyword(s):  
Shear Layer ◽  
Vortex Formation ◽  
Low Frequency ◽  
Frequency Component ◽  
Travelling Wave ◽  
Instability Wave ◽  
Spectral Content ◽  
Frequency Components ◽  
The Subject ◽  
Amplitude Growth

Oscillations of a cavity shear layer, involving a downstream-travelling wave and associated vortex formation, its impingement upon the cavity corner, and upstream influence of this vortex-corner interaction are the subject of this experimental investigation.Spectral analysis of the downstream-travelling wave reveals low-frequency components having substantial amplitudes relative to that of the fundamental (instability) frequency component; using bicoherence analysis it is shown that the lowest-frequency component can interact with the fundamental either to reinforce itself or to produce an additional (weaker) low-frequency component. In both cases, all frequency components exhibit an overall phase difference of almost 2kπ(k = 1, 2,…) between separation and impingement. Furthermore, the low-frequency and fundamental components have approximately the same amplitude growth rates and phase speeds; this suggests that the instability wave is amplitude-modulated at the low frequency, as confirmed by the form of instantaneous velocity traces.At the downstream corner of the cavity, successive vortices, arising from the amplified instability wave, undergo organized variations in (transverse) impingement location, producing a low-frequency component(s) of corner pressure. The spectral content and instantaneous trace of this impingement pressure are consistent with those of velocity fluctuations near the (upstream) shear-layer separation edge, giving evidence of the strong upstream influence of the corner region.

scholarly journals Rainfall and runoff forecasting with SSA–SVM approach

2001 ◽  
Vol 3 (3) ◽  
pp. 141-152 ◽  
Author(s):  
C. Sivapragasam ◽  
Shie-Yui Liong ◽  
M. F. K. Pasha
Keyword(s):  
Linear Prediction ◽  
Singular Spectrum Analysis ◽  
Low Frequency ◽  
Support Vector ◽  
Runoff Forecasting ◽  
Time Operation ◽  
Real Time Operation ◽  
Frequency Components ◽  
Hydrologic Variable ◽  
Original Time

Real time operation studies such as reservoir operation, flood forecasting, etc., necessitates good forecasts of the associated hydrologic variable(s). A significant improvement in such forecasting can be obtained by suitable pre-processing. In this study, a simple and efficient prediction technique based on Singular Spectrum Analysis (SSA) coupled with Support Vector Machine (SVM) is proposed. While SSA decomposes original time series into a set of high and low frequency components, SVM helps in efficiently dealing with the computational and generalization performance in a high-dimensional input space. The proposed technique is applied to predict the Tryggevælde catchment runoff data (Denmark) and the Singapore rainfall data as case studies. The results are compared with that of the non-linear prediction (NLP) method. The comparisons show that the proposed technique yields a significantly higher accuracy in the prediction than that of NLP.

scholarly journals Filter Characteristics in Image Decomposition with Singular Spectrum Analysis

2016 ◽  
Vol 08 (01) ◽  
pp. 1650002 ◽  
Author(s):  
Kenji Kume ◽  
Naoko Nose-Togawa
Keyword(s):  
Spectrum Analysis ◽  
Singular Spectrum Analysis ◽  
Low Frequency ◽  
Image Data ◽  
Original Data ◽  
Multidimensional Data ◽  
Singular Spectrum ◽  
Symmetry Properties ◽  
Frequency Components ◽  
Differential Type

Singular spectrum analysis is developed as a nonparametric spectral decomposition of a time series. It can be easily extended to the decomposition of multidimensional lattice-like data through the filtering interpretation. In this viewpoint, the singular spectrum analysis can be understood as the adaptive and optimal generation of the filters and their two-step point-symmetric operation to the original data. In this paper, we point out that, when applied to the multidimensional data, the adaptively generated filters exhibit symmetry properties resulting from the bisymmetric nature of the lag-covariance matrices. The eigenvectors of the lag-covariance matrix are either symmetric or antisymmetric, and for the 2D image data, these lead to the differential-type filters with even- or odd-order derivatives. The dominant filter is a smoothing filter, reflecting the dominance of low-frequency components of the photo images. The others are the edge-enhancement or the noise filters corresponding to the band-pass or the high-pass filters. The implication of the decomposition to the image denoising is briefly discussed.

scholarly journals An EEMD-Based Denoising Method for Seismic Signal of High Arch Dam Combining Wavelet with Singular Spectrum Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Bo Li ◽  
Lixin Zhang ◽  
Qiling Zhang ◽  
Shengmei Yang
Keyword(s):  
High Frequency ◽  
Singular Spectrum Analysis ◽  
Low Frequency ◽  
Arch Dam ◽  
Seismic Signals ◽  
High Arch Dam ◽  
Denoising Method ◽  
Arch Dams ◽  
Frequency Components ◽  
High Arch Dams

Due to complicated noise interference, seismic signals of high arch dam are of nonstationarity and a low signal-to-noise ratio (SNR) during acquisition process. The traditional denoising method may have filtered effective seismic signals of high arch dams. A self-adaptive denoising method based on ensemble empirical mode decomposition (EEMD) combining wavelet threshold with singular spectrum analysis (SSA) is proposed in this paper. Based on the EEMD result for seismic signals of high arch dams, a continuous mean square error criterion is used to distinguish high-frequency and low-frequency components of the intrinsic mode functions (IMFs). Denoised high-frequency IMF using wavelet threshold is reconstructed with low-frequency components, and SSA is implemented for the reconstructed signal. Simulation signal denoising analysis indicates that the proposed method can significantly reduce mean square error under low SNR condition, and the overall denoising effect is superior to EEMD and EEMD-Wavelet threshold denoising algorithms. Denoising analysis of measured seismic signals of high arch dams shows that the performance of denoised seismic signals using EEMD-Wavelet-SSA is obviously improved, and natural frequencies of the high arch dams can be effectively identified.

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

ANALYSIS OF STAND RESEARCH RESULTS OF AXIAL DYNAMIC FORCE IN DRILLING BY THREE ROLLER CONE BIT

2019 ◽  
pp. 81-93
Author(s):  
В. М. Мойсишин ◽  
M. V. Lyskanych ◽  
R. A. Zhovniruk ◽  
Ye. P. Majkovych
Keyword(s):  
Low Frequency ◽  
Maximum Energy ◽  
Dynamic Force ◽  
Low Frequency Oscillation ◽  
Drilling Tool ◽  
Rock Destruction ◽  
Frequency Components ◽  
Harmonic Components ◽  
Experimental Values ◽  
Harmful Effects

The purpose of the proposed article is to establish the causes of oscillations of drilling tool and the basic laws of the distribution of the total energy of the process of changing the axial dynamic force over frequencies of spectrum. Variable factors during experiments on the classical plan were the rigidity of drilling tool and the hardness of the rock. According to the results of research, the main power of the process of change of axial dynamic force during drilling of three roller cone bits is in the frequency range 0-32 Hz in which three harmonic frequency components are allocated which correspond to the theoretical values of low-frequency and gear oscillations of the chisel and proper oscillations of the bit. The experimental values of frequencies of harmonic components of energy and normalized spectrum as well as the magnitude of the dispersion of the axial dynamic force and its normalized values at these frequencies are presented. It has been found that with decreasing rigidity of the drilling tool maximum energy of axial dynamic force moves from the low-frequency oscillation region to the tooth oscillation area, intensifying the process of rock destruction and, at the same time, protecting the tool from the harmful effects of the vibrations of the bit. Reducing the rigidity of the drilling tool protects the bit from the harmful effects of the vibrations generated by the stand. The energy reductions in these fluctuations range from 47 to 77%.

A Novel Adaptive PET/CT Image Fusion Algorithm

2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai
Keyword(s):  
Lung Cancer ◽  
Image Fusion ◽  
High Frequency ◽  
Malignant Tumors ◽  
Low Frequency ◽  
Combination Method ◽  
Ct Image ◽  
Fusion Algorithm ◽  
Pet Ct ◽  
Frequency Components

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.

Underwater Image Enhancement Method Combining color and Luminance

2020 ◽  
Vol 13 ◽  
Author(s):  
ZHAO Baiting ◽  
WANG Feng ◽  
JIA Xiaofen ◽  
GUO Yongcun ◽  
WANG Chengjun
Keyword(s):  
Image Enhancement ◽  
Color Space ◽  
Low Frequency ◽  
Brightness Enhancement ◽  
Color Distortion ◽  
Underwater Image ◽  
Enhancement Method ◽  
Frequency Components ◽  
Image Contour ◽  
Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

Despeckling of Sar Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform

2020 ◽  
pp. 2150023
Author(s):  
Priya R. Kamath ◽  
Kedarnath Senapati ◽  
P. Jidesh
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Relevant Information ◽  
Detection Algorithm ◽  
Two Dimensional ◽  
Sar Images ◽  
S Transform ◽  
Processing Step ◽  
Frequency Components ◽  
Shock Filter

Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated.

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