scholarly journals Identification of magnetic anomalies of adjacent sourses using the wavelet transform modulus maxima and scale normalization

2018 ◽  
Vol 1 (6) ◽  
pp. 273-286
Author(s):  
Tin Quoc Chanh Duong ◽  
Dau Hieu Duong ◽  
Tan Minh Nguyen
Keyword(s):  
Wavelet Transform ◽  
Potential Field ◽  
Accurate Determination ◽  
Mekong Delta ◽  
Wavelet Transform Modulus Maxima ◽  
Correlative Function ◽  
Scale Normalization ◽  
Modeling Data ◽  
Set Up ◽  
Modulus Maxima

In the potential field inverse problems, accurate determination of the location for the anomaly sources and their properties played an important role. For geomagnetic anomalies of adjacent sources, they always superimpose upon each other not only in the spatial domain but also in the frequency domain, making the identification of these sources significantly problematic. In this paper, a new mother wavelet for effective analysis the properties of the close potential field sources was used. By theoretical modeling, using the wavelet transform modulus maxima (WTMM) method, we set up a correlative function between the scale parameter and geomagnetic source depth. Moreover, a scale normalization on the wavelet coefficients was introduced to enhancethe resolution for the separation of these sources in the scalograms, thereby determining their depth. After verifying the reliability of the proposed method on the modeling data, we have analysed the geomagnetic data in the Mekong delta. The results of this interpretation were consistency with previously published ones, furthermore, the level of resolution for this technique was quite coincidental with other methods using different geological data.

scholarly journals ỨNG DỤNG PHƯƠNG PHÁP CỰC ĐẠI WAVELET VÀ SỰ CHUẨN HÓA THAM SỐ TỈ LỆ ĐỂ XÁC ĐỊNH CÁC NGUỒN DỊ THƯỜNG TRỌNG LỰC LIỀN KỀ

2019 ◽  
Vol 19 (1) ◽  
pp. 163-177
Author(s):  
Tin Duong Quoc Chanh ◽  
Dau Duong Hieu
Keyword(s):  
Wavelet Transform ◽  
Potential Field ◽  
Mekong Delta ◽  
Gravity Anomalies ◽  
Potential Field Data ◽  
Wavelet Transform Modulus Maxima ◽  
Correlative Function ◽  
Modeling Data ◽  
Set Up ◽  
Modulus Maxima

Nowadays, the wavelet transform is frequently used in processing and interpretaion of potential field data, to detect accurately the location of the anomaly sources and their properties. For gravity anomalies of adjacent sources, they always superimpose upon each other not only in the spatial domain but also in the frequency domain, making the identification of these sources significantly problematic. In this paper, a new mother wavelet for effective analysis of the locations of the close potential field sources was introduced. By theoretical modeling, using the wavelet transform modulus maxima (WTMM) method, we set up a correlative function between the scale parameter and gravity source depth. Moreover, a scale normalization on the wavelet coefficients was applied to enhance resolution for the separation of these sources in the scalograms, thereby determining their depth. After verifying the reliability of the proposed method on the modeling data, we proposed a process for the location of the gravity anomalies of adjacent sources using the wavelet transform, and then application for analysing some of the gravity profiles in the Mekong Delta. The results of this interpretation were consistent with previously published results, but the level of resolution for this technique was quite coincidental with other methods using different geological data.

scholarly journals Interpretation of gravity anomaly data using the wavelet transform modulus maxima

2017 ◽  
Vol 17 (4B) ◽  
pp. 151-160
Author(s):  
Tin Duong Quoc Chanh ◽  
Dau Duong Hieu ◽  
Vinh Tran Xuan
Keyword(s):  
Wavelet Transform ◽  
Gravity Anomaly ◽  
Potential Field ◽  
Gravity Data ◽  
Mekong Delta ◽  
Theoretical Models ◽  
Potential Field Data ◽  
Wavelet Transform Modulus Maxima ◽  
Set Up ◽  
Modulus Maxima

Recently, the continuous wavelet transform has been applied for analysis of potential field data, to determine accurately the position for the anomaly sources and their properties. For gravity anomaly of adjacent sources, they always superimpose upon each other not only in the spatial domain but also in the frequency domain, making the identification of these sources significantly problematic. In this paper, a new mother wavelet function for effective analysis of the locations of the close potential field sources is used. By theoretical modeling, using the wavelet transform modulus maxima (WTMM) method, the relative function between the wavelet scale factor and the depth of gravity source is set up. In addition, the scale parameter normalization in the wavelet coefficients is reconstructed to enhance resolution for the separation of these sources in the scalogram, getting easy detection of their depth. After verifying the reliability of the proposed method on the theoretical models, a process for the location of the adjacent gravity sources using the wavelet transform is presented, and then applied for analyzing the gravity data in the Mekong Delta. The results of this interpretation are consistent with previously published results, but the level of resolution for this technique is quite coincidental with other methods using different geological data.

Study for Detection Algorithm of QRS Complex in ECG Signal

2013 ◽  
Vol 765-767 ◽  
pp. 2105-2108
Author(s):  
Xu Wen Li ◽  
Bi Wei Zhang ◽  
Qiang Wu
Keyword(s):  
Wavelet Transform ◽  
Detection Algorithm ◽  
Automatic Analysis ◽  
Detection Accuracy ◽  
Ecg Signal ◽  
Good Precision ◽  
Qrs Complex ◽  
Noise Interference ◽  
Wavelet Transform Modulus Maxima ◽  
Modulus Maxima

In ECG signals accurate detection to the position of QRS complex is a key to automatic analysis and diagnosis system. And its premise is that effectively remove all kinds of noise interference in ECG signal. Here, a method of detecting QRS based on EMD and wavelet transform was presented which is aim to improve the anti-noise performance of the detection algorithm. It is combined EMD with the theory of singularity detecting based on wavelet transform modulus maxima method. It has the high detection accuracy and good precision that can give an effective way to the automatic analysis for ECG signal.

The Type D Double-Ended Traveling-Wave Distance Protection for HVDC Based on Wavelet Transform

2013 ◽  
Vol 448-453 ◽  
pp. 2025-2029
Author(s):  
Ning Ye ◽  
Yan Ren ◽  
Dai Yin Fu
Keyword(s):  
Wavelet Transform ◽  
Traveling Wave ◽  
Distance Protection ◽  
Matlab Simulation ◽  
Hvdc System ◽  
Type D ◽  
Set Up ◽  
Modulus Maxima

This paper describes the modern Type D double-ended location principles and the wavelet modulus maxima theory and presents a principle and a scheme which bases on wavelet transform of the Type D double-ended traveling-wave distance protection for HVDC traveling line. Then set up a monopolar HVDC system and simulate it by PSCAD/EMTDC and Matlab. Simulation shows that this protection principle and scheme is right and feasible.

An Improved Denoising Method in RDTS Based on Wavelet Transform Modulus Maxima

2015 ◽  
Vol 15 (2) ◽  
pp. 1061-1067 ◽  
Author(s):  
Zongliang Wang ◽  
Guangping Lv ◽  
Jun Chang ◽  
Sasa Zhang ◽  
Sha Luo ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Denoising Method ◽  
Wavelet Transform Modulus Maxima ◽  
Modulus Maxima

Comparison and Improvements of Image Denoising Based on Wavelet Transform

2015 ◽  
Vol 740 ◽  
pp. 644-647
Author(s):  
Xue Mei Xiao
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Wavelet Analysis ◽  
Image Denoising ◽  
Wavelet Denoising ◽  
Important Application ◽  
Denoising Method ◽  
Advantages And Disadvantages ◽  
Wavelet Transform Modulus Maxima ◽  
Modulus Maxima

Wavelet transform denoising is an important application of wavelet analysis in signal and image processing. Several popular wavelet denoising methods are introduced including the Mallat forced denoising, the wavelet transform modulus maxima method and the nonlinear wavelet threshold denoising method. Their advantages and disadvantages are compared, which may be helpful in selecting the wavelet denoising methods. At the same time, several improvement methods are offered.

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