• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.943-946
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• 2000

기계설비의 진동신호와 음향신호에서 결함신호를 검출하기 위해 본 논문에서는 ALE와 트리구조 필터뱅크를 이용 진동분석 시스템을 설계 구현하였다. ALE는 신호를 전처리함으로서 진동신호의 주기성분을 제거하여 결함신호검출을 용이하게 하며 트리구조 필터뱅크는 비정제적 결함신호를 전 대역에서 동일한 분해도로 분해한다. 설계된 진동분석 시스템은 모의실험과 DSP상의 구현을 통해 그 성능이 평가하였다.

• The Journal of the Acoustical Society of Korea
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• v.24 no.7
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• pp.416-422
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• 2005

Speech recognition in digital communication systems has very low performance due to the spectral distortion caused by speech codecs. In this paper, the spectral distortion by speech codecs is analyzed and a pre-processing method which compensates for the spectral distortion is proposed for performance enhancement of speech recognition. Three standard speech codecs. IS-127 EVRC. ITU G.729 CS-ACELP and IS-96 QCELP. are considered for algorithm development and evaluation, and a single method which can be applied commonly to all codecs is developed. The performance of the proposed method is evaluated for three codecs, and by using the speech features extracted from the compensated spectrum. the recognition rate is improved by the maximum of $15.6\%$ compared with that using the degraded speech features.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06e
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• pp.169-172
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• 1998

본 논문에서는 ATW(Automatic Tracking Window)를 사용하여 입력신호를 처리한 후에 MUSIC을 사용하여 주파수를 추정하도록 알고리즘을 수정하므로써 MUSIC알고리즘의 Threshold효과를 개선할 수 있음을 보인다[1]. ATW 전처리는 일종의 대역 여파기 효과를 가지나 일반 대역 여파기와 다른 점은 사용자가 입력신호의 중심 주파수를 알지 못해도 된다는 장점을 갖는다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.41-44
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• 2022

Mean-Shift 영상 분할은 객체 검출을 위한 영상 전처리 방법으로써, 영상 처리 및 패턴 인식 분야에서 널리 사용되는 방법이다. 영상 분할은 영역 기반과 에지 기반 방식으로 나누어지며 대표적으로 FCM, Quickshift, Felzenszwalb, SLIC 알고리즘 등 이 있다. 언급한 영상 분할 방법들은 Mean-Shift 영상 분할에 비해서 빠른 속도로 실행시킬 수 있지만, 형태적 특징이 훼손되고 하나의 객체가 여러 세그멘테이션으로 분할된다는 단점을 가지고 있다. 본 논문에서는 소형 객체를 탐지하기 위한 고속화된 Mean-Shift 영상 분할과 객체의 형태적 특징을 이용하여 객체를 탐지하는 방법을 제안한다. 하드웨어 리소스가 제한된 신호처리기에 제안하는 알고리즘을 수행하기 위하여 Mean-Shift 영상 분할에서 필터링 과정을 고속화 하였고, 적외선 영상 내 영상 전처리 수행을 통해 잡음 제거 후 Mean-Shift 영상 분할 방법을 수행함으로써, 객체의 형태적 특징을 잘 살려서 영상 분할을 할 수 있도록 하였다. 또한 각 세그멘테이션의 크기, 너비, 높이, 밝기 정보와 형태적 특징점을 이용한 객체 탐지 방법을 제안한다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.5
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• pp.145-151
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• 1989

A new preprocess technique is presented which can improve the routing efficiency in the gate array layout designs. In order to resolve the cycle problem in the detailed routing, we exchange the logically equivalent pins in each channel. The signal nets are divided, and doubly connected signal net components are removed, so that the increase in the number of tracks can be controlled.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2012.06a
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• pp.168-168
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• 2012

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.5
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• pp.380-388
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• 2019

Jet engine modulation(JEM) signals are widely used for target recognition. These signals coming from a potentially hostile aircraft provide specific information about the jet engine. In order to obtain the number of blades, which is uniquely provided by the JEM signal, one must extract the spool rate, which is the rotation speed of the blades. In this paper, we propose an algorithm to extract the spool rate from a weak JEM signal. A criterion is developed to extract the spool rate from the JEM signal by analyzing the intensity of the JEM signal component. The weak signal is first subjected to a high-pass filtering-based process, which modifies it to facilitate spool rate extraction. We then apply a peak detection process and extract the spool rate. The technique is simpler than the existing CEMD or WD method, is accurate, and greatly reduces the time required.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.249-253
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• 2002

레이더 기술은 획득된 신호를 바탕으로 물체(object)를 추출, 추적함으로써 자동항해시스템, 항공기 충돌방지시스템 둥의 각종 첨단 분야에 두루 활용되고 있으며, 산업 전반에 걸쳐 눈부신 발전을 거듭해 왔다. 본 논문에서는 레이더로부터 획득한 신호로부터 효율적인 물체를 추출, 추적하기 위한 전처리 단계로서 레이더 이미지를 구성하는 방법에 대해 제안한다. 특히, 불완전한 데이터 시퀀스를 갖는 신호를 양질의 레이더 이미지로 복원하는 방법을 제안하고 결과 영상을 통해 제안하는 방법의 우수성을 검증하였다.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.595-602
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• 2007

This paper proposes a method that discriminates signal peptide and predicts the cleavage site of the secretory proteins cleaved by the signal peptidase I. The preprocessing stage uses hydrophobicity scales of amino acids in order to predict the presence of signal sequence and the cleavage site. The preprocessing enhances the performance of the prediction method by eliminating the non-secretory proteins in the early stage of prediction. for the effective use of support vector machine for the signal sequence prediction, the biologically relevant distance between the amino acid sequences is defined by using the hydrophobicity and substitution matrix; the hydrophobicity can be used to Predict the location of amino acid in a cell and the substitution matrix represents the evolutionary relationships of amino acids. The proposed method showed 98.9% discrimination rates from signal sequences and 88% correct rate of the cleavage site prediction on Swiss-Prot release 50 protein database using the 5-fold-cross-validation. In the comparison tests, the proposed method has performed significantly better than other prediction methods.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.109-121
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• 2024

In various manufacturing processes such as textiles and automobiles, when equipment breaks down or stops, the machines do not work, which leads to time and financial losses for the company. Therefore, it is important to detect equipment abnormalities in advance so that equipment failures can be predicted and repaired before they occur. Most equipment failures are caused by bearing failures, which are essential parts of equipment, and detection bearing anomaly is the essence of PHM(Prognostics and Health Management) research. In this paper, we propose a preprocessing algorithm called SWT-SVD, which analyzes vibration signals from bearings and apply it to an anomaly transformer, one of the time series anomaly detection model networks, to implement bearing anomaly detection model. Vibration signals from the bearing manufacturing process contain noise due to the real-time generation of sensor values. To reduce noise in vibration signals, we use the Stationary Wavelet Transform to extract frequency components and perform preprocessing to extract meaningful features through the Singular Value Decomposition algorithm. For experimental validation of the proposed SWT-SVD preprocessing method in the bearing anomaly detection model, we utilize the PHM-2012-Challenge dataset provided by the IEEE PHM Conference. The experimental results demonstrate significant performance with an accuracy of 0.98 and an F1-Score of 0.97. Additionally, to substantiate performance improvement, we conduct a comparative analysis with previous studies, confirming that the proposed preprocessing method outperforms previous preprocessing methods in terms of performance.