Proposed Subtraction Method Research Articles

Noise subtraction from KAGRA O3GK data using Independent Component Analysis

During April 7–21 2020, KAGRA conducted its first scientific observation in conjunction with the GEO600 detector. The dominant noise sources during this run were found to be suspension control noise in the low-frequency range and acoustic noise in the mid-frequency range. In this study, we show that their contributions in the observational data can be reduced by a signal processing method called independent component analysis (ICA). The model of ICA is extended from that studied in the initial KAGRA data analysis to account for frequency dependence, while the linearity and stationarity of the coupling between the interferometer and the noise sources are still assumed. We identify optimal witness sensors in the application of ICA, leading to successful mitigation of these two dominant contributions. We also analyze the stability of the transfer functions for the entire two weeks of data to investigate the applicability of the proposed subtraction method in gravitational wave searches.

An Effective Procedure for Supplier Selection Applied to Glass Substrate Processes with Multiple Lines

In this paper, we consider a supplier selection problem, which compares two glass substrate processes with multiple lines and selects the one that has a higher capability. A test statistic obtained by a subtraction method is employed to establish a hypothesis test with two phases. Critical values of the test are obtained to determine the selection decisions. Sample sizes required for various designated selection powers and confidence levels are also investigated. Practitioners can use the proposed method to make reliable decisions. This paper presents a real-world case of a glass substrate process. The selection procedure uses data to reach a decision in supplier selection. We compare the results of the division method to the proposed subtraction method. The results show that the proposed subtraction method is indeed more powerful than the division method.

An effective powerful test for one-sided supplier selection problem

In this paper, we consider the supplier selection problem, which deals with comparing two one-sided processes and selecting a better one that has a higher capability. We first review two existing approximation approaches, and an exact approach proposed which we refer to as the division method. We then develop a new exact approach called the subtraction method. We compare the two exact methods on the selection power. The results show that the proposed subtraction method is indeed more powerful than the division method. A two-phase selecting procedure is then developed based on the subtraction method for practical applications. Some computational results are tabulated for practitioners’ convenience.

ECG 신호의 가변적인 전력선 잡음 제거를 위한 적응형 차감기법

전력선 잡음은 ECG 신호 분석에 있어 특정 구간의 왜곡을 발생시킬 수 있다. 특히 P와 R파와 같이 부정맥 진단에 중요한 요소가 되는 구간은 전력선 주파수가 샘플링 주파수의 배수(multiple)일 경우와 그렇지 않을 경우에 각각 다른 형태의 잡음으로 나타나며, 잡음의 특성 또한 선형과 비선형으로 나누어진다. 본 논문에서는 ECG 신호의 가변적인 전력선 잡음 제거를 위한 적응형 차감 기법을 제안한다. 제안한 방법은 먼저 전력선 주파수와 샘플링 주파수와의 배수 관계를 multiple과 non-multiple로 구분한 후 각 구간에 대한 선형성 여부를 판단한다. 이후 선형 구간은 이동평균 필터를 이용하여 잡음성분을 추출하고, 비선형 구간 잡음은 선형구간에서 추출되어 임시버퍼에 저장된 잡음 성분을 이용하여 추출한다. 제안한 기법의 P파와 R파 검출성능을 평가하기 위해 MIT-BIH 데이터베이스의 119번 레코드를 사용하였다. 실험 결과 기존 노치 필터의 경우 P파 97.91%, R파 96.66%, 제안한 차감기법의 경우 P파 99.01%, R파 97.93%의 검출결과를 나타내었다. Power-line interference(PLI) can distort certain regions in analysing the ECG signal. In particular, the regions such as P and R wave that are important element in diagnosing with arrhythmia is expressed as different type of noise according to the case whether power-line frequency is multiples of sampling frequency and or not. Noise characteristics is also divided into linearity and non-linearity. In this paper, adaptive subtraction method for removing variable PLI of ECG signal is proposed. We classify the multiple relationship between power line and sampling frequency as Multiple and Non-multiple. PLI of Linear segment is extracted through moving average filter, PLI of non-linear segment is extracted through the interference component that is extracted in the linear segment and stored in the temporary buffer. The performance of P wave and R wave detection is evaluated by using 119 data record of MIT-BIH arrhythmia database. The achieved scores indicate P wave detection rate of 97.91%, R wave detection rate of 96.66% and P wave detection rate of 99.01%, R wave detection rate of 97.93% accuracy respectively for Notch filter and proposed subtraction method.

Attenuation of seismic water-column noise, tested on seismic data from the Grane field

Seismic analysis of long-offset data is gaining increased attention for several purposes: constraining three-parameter amplitude variation with offset (AVO) methods, 4D analysis, and imaging below salt and basalt. A major challenge for exploiting long-offset seismic data is that the water-column noise mixes with and distorts the reflected seismic signal from interfaces at the target level. Traditional processing methods such as [Formula: see text] filtering often reduce this distortion problem. This article offers an alternative to conventional processing methods. The alternative exploits the difference in water depth and reservoir depth to subtract water-column noise. The proposed subtraction method works well where water depth is constant. The method was tested on a multicomponent seismic data set from the Grane field (North Sea). In this location, the water depth is fairly constant over the field. The fieldwise similarity level of water-column noise is high. A comparison of the water-column noise from various locations shows that the similarity is 10%, measured in normalized root mean squared error. The fact that the water-column noise is highly repeatable is a strong indication that the major part of it is harmonic waves that propagate in the water layer.

Reduction of matched‐field sidelobes by subtraction of cross‐spectral matrix elements associated with strong signals

Matched‐field processing can be used to locate a sound source in the ocean by finding the best correlation between the signals received by a set of hydrophones and expected signals that would be received if the sound source were at a particular location. When standard (Bartlett) correlations are used, the sidelobes of a strong source may obscure the main response of a weaker source. A simple palliative for this problem is to calculate the elements of the cross‐spectral matrix associated with the strongest signal and subtract these from the observed cross‐spectral matrix. This process can be repeated for the next strongest signal, etc. This method has been suggested before for use with conventional plane‐wave beamforming [H. P. Bucker, J. Acoust. Soc. Am. 62, 1222–1225 (1977)]. In this report, the sidelobe reduction is quantified as function of mismatch in the environmental parameters and the proposed subtraction method is compared to high‐resolution adaptive matched‐field algorithms.