• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.199-205
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• 2005

When recording single-unit responses from neural systems, a common problem is the accurate detection of spikes (action potentials) in the presence of competing unwanted (noise) signals. While some sources of noise can be readily dealt with through filtering or 'template subtraction' techniques, other sources present a more difficult problem. In particular, noise components introduced by power supplies, which contain harmonics of the power-line frequency, can be particularly troublesome in that they can mimic the shape of the desired spikes. Thus, standard 'template subtraction' techniques or notch-filtering approaches are not appropriate. In this study, we propose the use of a novel template-subtraction scheme that involves estimating the power-line noise waveform and using cross-correlation techniques to subtract them from the recordings. This technique requires two key steps: (1) cross-correlation analysis of each recorded waveform extracts a robust representation of the power-line noise waveform and (2) a second level of cross-correlation to successfully subtract that representation from each recorded waveform. This paper describes this algorithm and provides examples of its implementation using actual recorded waveforms that are contaminated with these noise signals. An improvement (reduction) in the noise level is reported, as are suggestions for future implementation of this strategy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.728-732
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• 2010

GIS(Gas insulated switching gear) is power equipment with excellent dielectric strength and is economy merit in high confidence and stability. Recently, because equipment of GIS was occurring problem of confidence used for a long time, partial discharge on-line diagnosis systems have been importantly recognized. Partial discharge (PD) detection is an effective means for monitoring and evaluation of dielectric condition of gas insulated system (GIS). The ultra-high-frequency (UHF) PD detection technique can detect and locate the PD sources inside GIS by detecting electromagnetic wave emitted from PD source. Therefore, real-time diagnostic system using UHF detection method has been developed for this application is being expanded gradually. However, the signal of partial discharge occurring in SF6 gas is very weak and susceptible to external noises which mainly consist of PD in air. Thus, it is important to distinguish the PD in SF6 gas more sensitively from the external noises. Unfortunately, these external noise signals and the partial discharge signals have very similar characteristics. Therefore, to solve this problem, we need the signal processing method for distinguish partial discharge signals with external noise signals for improvement of SNR(signal to noise ratio) and sensitivity. In this paper, we proposed internal signal processing method for removing external noise signals with built-in pre.amplifier and frequency conversion circuit.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.446-454
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• 2002

This paper presents the Doppler Scanning technique which enables us to detect the relative positions of moving distributed sources using Doppler frequency shift estimate when the moving source consists of distributed sources with different signature frequencies. Doppler frequency shifts of characteristic frequencies of machinery noise sources such as ship's generator and propeller, with tine along CPA (Closest Point of Approach of moving source) are unique, and can be functioned with respect to each source position. Therefore, this technique can be applied to estimate the relative geometrical positions between machinery noise sources. The Extended Kalman Filter (EKF) which has a high frequency resolution with high time resolution, is adopted for improving accuracy of Doppler frequency shift estimate geometric resolution of machinery positions since machinery noise sources show in general low frequency band characteristics with limited spacial distance. The performance of the technique is examined by the numerical simulations and is verified by the experiment using loudspeaker sources on the roof of the car.

• Journal of IKEEE
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• v.23 no.1
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• pp.310-313
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• 2019

This paper used the majority function to digitally filter back-electromotive force as an explanation of the Brushless DC MOTOR control algorithm. The cause and improvement of motor noise, which are operating in close proximity to high frequency sources, did not use conventional low pass filter and comparator elements. Also, they repeatedly output a noise-free BEMF signal for the input value of the majority detection filtering. These filtering steps can help reduce costs and minimize the area of a PCB by requiring relatively little hardware.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.481-486
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• 2012

Accurate and efficient estimation of the number of sources is critical for providing the parameter of targets in problems of array signal processing and blind source separation among other such problems. When conventional estimators work in unfavorable scenarios, e.g., at low signal-to-noise ratio (SNR), with a small number of snapshots, or for sources with a different strength, it is challenging to maintain good performance. In this paper, the detection limit of the minimum description length (MDL) estimator and the signal strength required for reliable detection are first discussed. Though a comparison, we analyze the reason that performances of classical estimators deteriorate completely in unfavorable scenarios. After discussing the limiting distribution of eigenvalues of the sample covariance matrix, we propose a new approach for estimating the number of sources which is based on a sequential hypothesis test. The new estimator performs better in unfavorable scenarios and is consistent in the traditional asymptotic sense. Finally, numerical evaluations indicate that the proposed estimator performs well when compared with other traditional estimators at low SNR and in the finite sample size case, especially when weak signals are superimposed on the strong signals.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.7
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• pp.532-538
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• 2003

This paper studies on the noise reduction for a small automobile DC Motor (a window motor) using the 6 sigma process. The application of 6 sigma process suggested reliable and valuable statistical data for the quality of the DC motor at the production line. In the measurement step in 6 sigma process. the FMEA(failure mode effect analysis) were used for the detection of noise sources. The application of 6 sigma Process gave not only the improving method for the quality of the DC motor but also the confidence of improvement Itself since it was done on the basis of the test results for a number of DC motors at the production line. Consequently the 6 sigma process was proved very effective for the noise reduction at the production line.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.509-514
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• 2002

This paper studies on the noise reduction for a small automobile DC Motor (a window motor) using the 6 sigma process. The application of 6 sigma process suggested reliable and valuable statistical data for the quality of the DC motor at the production line. In the measurement step in 6 sigma process, the FMEA(Failure Mode Effect Analysis) were used for the detection of noise sources. The application of 6 sigma process gave not only the improving method for the quality of the DC motor but also the confidence of improvement itself since it was done on the basis of the test results for a number of DC motors at the production line. Consequently the 6 sigma process was proved very effective for the noise reduction at the production line.

• Journal of Biomedical Engineering Research
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• v.34 no.4
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• pp.204-211
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• 2013

In this paper, an algorithm for suppressing acoustic noises contained in stethoscope sound is proposed and implemented in real-time using an embedded DSP system. Sound collected by stethoscope is down-sampled and band-pass filtered, and later an NLMS adaptive filter is used to cancel the acoustic noise induced from external noise sources. Also, the unpredictable impulsive noises due to fabric friction and instantaneous tapping are detected using the SD-ROM algorithm, and suppressed using an algorithm approximating the morphology filter. The proposed algorithm was tested using signals collected with a digital stethoscope mockup, and implemented on an ARM920T-based DSP system.

• Analytical Science and Technology
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• v.35 no.2
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• pp.69-81
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• 2022

The method of measuring and classifying the energy category of neutrons directly using raw data acquired through a CZT detector is not satisfactory, in terms of accuracy and efficiency, because of its poor energy resolution and low measurement efficiency. Moreover, this method of measuring and analyzing the characteristics of low-energy or low-activity gamma-ray sources might be not accurate and efficient in the case of neutrons because of various factors, such as the noise of the CZT detector itself and the influence of environmental radiation. We have therefore developed an efficient method of analyzing radiation characteristics using a neutron and gamma-ray analysis algorithm for the rapid and clear identification of the type, energy, and radioactivity of gamma-ray sources as well as the detection and classification of the energy category (fast or thermal neutrons) of neutron sources, employing raw data acquired through a CZT detector. The neutron analysis algorithm is based on the fact that in the energy-spectrum channel of 558.6 keV emitted in the nuclear reaction ¹¹³Cd + ¹n → ¹¹⁴Cd + in the CZT detector, there is a notable difference in detection information between a CZT detector without a PE modulator and a CZT detector with a PE modulator, but there is no significant difference between the two detectors in other energy-spectrum channels. In addition, the gamma-ray analysis algorithm uses the difference in the detection information of the CZT detector between the unique characteristic energy-spectrum channel of a gamma-ray source and other channels. This efficient method of analyzing radiation characteristics is expected to be useful for the rapid radiation detection and accurate information collection on radiation sources, which are required to minimize radiation damage and manage accidents in national disaster situations, such as large-scale radioactivity leak accidents at nuclear power plants or nuclear material handling facilities.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.79-87
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• 2009

This paper reviews several multi-source localization methods which estimate ITDs based on zero crossings (ZCs). Employing signal-to-noise ratio (SNR) estimation from ITD variances, these ZC-based source localization methods are more robust to diffuse noise than the cross-correlation (CC)-based one with less computational complexity. In order to take reverberant environments into account, two approaches detect intervals which dominantly contain direct-path components from sources to sensors because they may effectively provide reliable ITDDs corresponding to source directions. One accomplishes the detection by comparing the original and cepstral-prefiltering-processed envelopes, and the other searches sudden increase of acoustic energy by considering typical characteristics of acoustic reverberation. Experiments for comparison of these methods demonstrate that the approach with energy-based detection efficiently achieves multi-source localization in reverberant environments.