• The Journal of Engineering Research
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• v.8 no.1
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• pp.59-65
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• 2006

본 논문에서는 마이크로폰 어레이 시스템을 이용하여 여러 화자의 음성 정보로부터 각 화자가 위치한 방향을 추정하는 기술 개발 내용을 다룬다. 성능 향상을 위한 전처리 과정으로 비선형 증폭기를 사용하여 거리에 따른 영향을 최소화하는 과정과 잡음에 대한 강인성을 얻기 위해 음성활성 영역을 검출하는 과정을 포함한다. 등간격으로 배치된 마이크로폰 어레이 시스템의 기하학적 특성에 따른 음원의 위치와 신호의 지연시간차이와의 상관관계로부터 화자의 위치를 역으로 추정하는 알고리즘을 기본으로 하여 가능성 척도를 계산하고 이를 활용하여 가능성이 높은 것들을 클러스터링하여 가능성이 있는 후보를 선정하여 화자의 방향을 검지한다. 이 과정에서 오인식을 최소화하기 위하여 가능성이 희박한 영역에 대한 추정 억제 방법으로 부정식 추론법을 적용하였다. 2 화자의 음성 신호를 입력으로 한 실험을 통하여 제안한 방법에 의한 다화자 방향검지의 가능성을 알아보았다.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.127-130
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• 2007

The conventional feature recombination technique is very effective in the band-limited noise condition, but in broad-band noise condition, the conventional feature recombination technique does not produce notable performance improvement compared with the full-band system. To cope with this drawback, we introduce a new technique of sub-band likelihood computation in the feature recombination, and propose a new feature recombination method by using this sub-band likelihood computation. Furthermore, the reliable sub-band selection based on the signal-to-noise ratio is used to improve the performance of this proposed feature recombination. Experimental results shows that the average error reduction rate in various noise condition is more than 27% compared with the conventional full-band speaker identification system.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1294-1295
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• 2015

BLDC 모터는 고효율, 비 관성에 의한 큰 토크, 제어의 단순성과 같은 뚜렷한 장점들 때문에 일반적으로 로봇공학 및 항공 우주, 자동차 같은 응용 분야에 널리 사용된다. 따라서 사용자가 원하는 속도를 일정하게 유지하는 것은 중요하다. BLDC 모터는 무게 변화와 같은 파라미터 변화나 센서 잡음, 외부환경 변화에 따른 외란의 영향이 항상 존재하게 된다. 하지만 일반적인 제어기 설계방법으로는 파라미터 변화, 센서 잡음이나 외란의 영향에 효과적으로 대응하는 것이 쉽지 않다. 본 논문에서는 강인 제어 기법 중 하나인 H-infinity 제어기법을 BLDC 모터에 적용하여 속도제어기를 설계하였다. 또한 DSP 구현을 통하여 일반적으로 널리 사용되는 PI 제어기와의 비교를 통해 H-infinity 속도 제어기의 우수성을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.11A
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• pp.1672-1681
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• 2000

초광대역 시간 도약 이전 임펄스 무전 전송 시스템의 성능 평가 1672 최근 들어 실내 무선 LAN(local area network)이나 군용 무선 통신 시스템을 위한 새로운 대역 확산 전송방식으로서 초광대역 시간 도약 임펄스 무선 전송(ultra wideband time hopping impulse radio; 이하 IR) 기술이 큰 관심을 모으고 있다. 신호 전송을 위해 연속적인 정현파를 이용하는 기존의 무선 전송 시스템과는 달리 IR 시스템은 1 nese 이하의 매우 짧은 펄스폭의 펄스 위치 변조(pulse position modulation)된 가우시안 모노사이클 멀스 열을 이용하므로서 매우 작은 크기의 수 GHz에 이르는 초광대역 스펙트럼을 가지며 기존의 통신 시스템에 거의 간섭을 미치지 않으며 사용 가능하다. 본 논문에서는 동기식 이진 (synchronous binary) IR 시스템의 성능 분석 및 평가 결과를 제시하고자 한다.이를 위해 의사 잡음 부호 발생기와 decimator로 구성된 시간 도약 패턴을 사용 하여 다원 접속 간섭 이 배제되는 동기식 이진 IR 시스템의 비트 오율에 대한 closed form 결과를 유도하고, 유도된 이론적인 성능 결과를 부가성 백색 가우시안 잡음 채널에 대한 모의 실험을 통해 확인하였다. 또한 모의 실험을 통해 상관 복조기에서 발행한 렌덤 타이밍 지터에 대해 IR 시스템의 강인한 특성을 확인하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.4
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• pp.361-369
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• 2002

In order to extract motion features from an input image acquired by a static CCD-camera in a restricted area, we need a robust algorithm to cope with noise sensitivity and condition change. In this paper, we proposed an efficient algorithm to extract and track motion features in a noisy environment or with sudden condition changes. We extract motion features by considering a change of neighborhood pixels when moving objects exist in a current frame with an initial background. To remove noise in moving regions, we used a morphological filter and extracted a motion of each object using 8-connected component labeling. Finally, we provide experimental results and statistical analysis with various conditions and models.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.169-174
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• 2010

This paper explains end-point detection method for better speech recognition rates. The proposed method determines speech and non-speech region with the entropy and the harmonic detection of speech. The end-point detection using entropy on the speech spectral energy has good performance at the high SNR(SNR 15dB) environments. At the low SNR environment(SNR 0dB), however, the threshold level of speech and noise varies, so the precise end-point detection is difficult. Therefore, this paper introduces the end-point detection methods which uses speech spectral entropy and harmonics. Experiment shows better performance than the conventional entropy methods.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.268-272
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• 2009

In this paper, we propose a Gaussian Mixture Model (GMM) based incremental robust adaptation with a forgetting factor for the speaker verification. Speaker recognition system uses a speaker model adaptation method with small amounts of data in order to obtain a good performance. However, a conventional adaptation method has vulnerable to the outlier from the irregular utterance variations and the presence noise, which results in inaccurate speaker model. As time goes by, a rate in which new data are adapted to a model is reduced. The proposed algorithm uses an incremental robust adaptation in order to reduce effect of outlier and use forgetting factor in order to maintain adaptive rate of new data on GMM based speaker model. The incremental robust adaptation uses a method which registers small amount of data in a speaker recognition model and adapts a model to new data to be tested. Experimental results from the data set gathered over seven months show that the proposed algorithm is robust against outliers and maintains adaptive rate of new data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.121-130
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• 2005

In this paper, we propose a feature extraction method for iris recognition using wavelet transforms. The wavelet transform is fast and has a good localization characteristic. In particular, the low frequency band can be used as an effective feature vector. In iris recognition, the noise caused by eyelid the eyebrow, glint, etc may be included in iris. The iris pattern is distorted by noises by itself, and a feature extraction algorithm based on filter such as Wavelets, Gabor transform spreads noises into whole iris region. Namely, such noises degrade the performance of iris recognition systems a major problem. This kind of noise has adverse effect on performance. In order to solve these problems, we propose to divide the iris image into a number of sub-region and apply the wavelet transform to each sub-region. Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform and region division noticeably improves recognition performance. However, it is noted that the processing time of the wavelet transform is much faster than that of the existing methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.469-474
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• 2011

This paper presents the intelligent tracking method for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. K-means clustering and TS fuzzy system are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by K-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. While calculating expected value, the non-linearity of the maneuvering target is recognized as linear one by dividing acceleration and the capability of Kalman filter is kept in the filtering process. The error for the non-linearity is compensated by approximated acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.40-47
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• 2009

A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.