• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.1
• /
• pp.209-213
• /
• 2010

In this paper, an efficient predictor for entropy coding is proposed. It adaptively selects one of two prediction errors obtained by MED(median edge detector) or GAP(gradient adaptive prediction). The reduced error is encoded by existing entropy coding method. Experimental results show that the proposed algorithm can compress higher than existing predictive methods.

• Proceedings of the Acoustical Society of Korea Conference
• /
• autumn
• /
• pp.261-264
• /
• 2004

본 논문에서 는 muti-channel lattice 예측기를 사용하여 AP(affine projection) 알고리듬을 근사적으로 구현하는 알고리즘을 제안한다. Lattice 예측기의 예측 오차를 사용하여 TDL 필터 계수를 적응적으로 조정함으로써 AP 알고리듬을 근사화한다. 또한 전처리단으로 사용된 lattice 예측기를 TDL 필터와 결합함으로써 기존의 방법보다 계산량을 더욱 줄일 수 있는 알고리듬을 제안한다. 제안된 알고리즘은 기존의 알고리즘보다 적은 계산량을 필요로 하지 만 AP 알고리즘을 보다 근사적으로 구현할 수 있다는 장점이 있다.

• Journal of the Korea Society of Computer and Information
• /
• v.10 no.2 s.34
• /
• pp.21-30
• /
• 2005

In general, the robust estimation method is well known for a good statistical estimator that is insensitive to small departures from the idealized assumptions for which the estimation is optimized. While there are many existing robust estimation techniques that have been proposed in the literature, two main techniques used in computer vision are M-estimators and least-median of squares (LMS). Among these. we utilized the M-estimators since they are known to provide an optimal estimation of affine motion parameters. The M-estimators have higher statistical efficiency but tolerate much lower percentages of outliers unless properly initialized. To resolve these problems, we proposed an adaptive M-estimators algorithm that effectively separates outliers from non-outliers and estimate affine model parameters, using a continuous sigmoid weight function. The experimental results show the superiority of our method.

• Journal of the Korea Society for Simulation
• /
• v.25 no.3
• /
• pp.65-76
• /
• 2016

Self-adaptive software is software that adapts by itself to system requirements about the recognized problems without stopping the software cycle. In order to reduce the unnecessary adaptation in the system having the critical points, we propose proactive approach which can predict the future operation after a critical point. In this paper, we predict the future operation after a critical point using a hybrid model to deal with the characteristics of the observed data with the linear and non-linear pattern. The operation of the prediction method is determined on a timing decision indicator based on the prediction accuracy. The two main points of contributions of this paper are to reduce uncertainty about the future operation by predicting the situation after a critical point using hybrid model and to reduce unnecessary adaptation implementation by deciding a timing based on a timing decision indicator.

• Journal of Digital Convergence
• /
• v.15 no.7
• /
• pp.307-317
• /
• 2017

This study was to identify the factors influencing college life adjustment and sub-scales of nursing students. Self- report questionnaire surveys were conducted toward 282 freshman nursing students to measure college life adjustment, psychological well-being, emotional intelligence, and self-efficacy. Data were collected from September 22 through October 7, 2016. This study was analyzed using SPSS Win 18.0. The average mean of college life adjustment was 3.36 and academic activity was the highest, followed by individual psychology, social experience, Interpersonal relationship, and career preparation. A correlation of psychological well-being, emotional intelligence, self-efficacy, college life adjustment and sub-scales showed positive correlation. The strongest predictor of college life adjustment was a self-efficacy. And sub-scales, the strongest predictor of academic activity was academic achievement, career preparation was self-efficacy, individual psychology and social experience was emotional intelligence, and Interpersonal relationship was psychological well-being. An intervention program which includes these significant variables of subjects is essential to improve of college life adjustment.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.15 no.3
• /
• pp.809-823
• /
• 1991

본 연구에서는 Wiener 필터링 이론에 의하여 소음원의 입력신호에 대한 최적 한 예측을 할 수 있는 최적예측기(optimal predictor)로써 부가적인 음을 발생시키고 입력신호 및 출력신호 간의 차인 오차를 최소화시키도록 하는 적응신호처리방법에 대 해 설명하고 이러한 적응 신호처리 방법을 이용한 능동 소음 제어 방법을 제시하였다. 이와 아울러 제어계의 환경 변화에 따른 파라메타의 변화에 적응적으로 응답이 가능해 야 하는 적응 소음 제어계에서, 음향궤환과 함께 필히 고려해야하는 부가적인 전달함 수-모델과 스피커를 포함하는 보조경로 및 오차미이크로폰을 포함하는 오차경로의 전 달함수의 영향을 고려한 능동소음제어에 대해 연구하였다.

• Proceedings of the IEEK Conference
• /
• 2000.09a
• /
• pp.113-116
• /
• 2000

본 논문에서는 probabilistic principal component analysis (PPCA)를 이용하여 extended maximum a posteriori (EMAP)에 기반한 화자적응 시스템의 성능을 향상시키는 방법을 제시하고자 한다. PPCA는 각각의 hidden Markov model (HMM) 사이의 상관계수 행렬을 강인하게 예측하는데 적용된다. 이렇게 구한 상관계수 행렬은 화자적응 시스템에 사용된다. PPCA는 연산이 효율적이고, EMAP에서 기존에 사용되었던 방법에 비해 향상된 성능을 보여준다. 여러 차례의 음성인식 실험을 통하여, PPCA를 적용한 EMAP은 적은 양의 적응 데이타에서 좋은 성능을 보인다는 것을 확인할 수 있다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.10 no.12
• /
• pp.1329-1336
• /
• 2015

Due to the advances in hardware technologies for low-power CMOS cameras, there have been various researches on wireless video sensor network(WVSN) applications including agricultural monitoring and environmental tracking. In such a system, its core technologies include video compression and wireless transmission. Since data of video sensors are bigger than those of other sensors, it is particularly necessary to estimate precisely the traffic after video encoding. In this paper, we present an estimation method for the encoded video traffic in WVSN networks. To estimate traffic characteristics accurately, the proposed method first measures complexities of frames and then applies them to the bit rate estimation adaptively. It is shown by experimental results that the proposed method improves the estimation of bit rate characteristics by more than 12% as compared to the existing method.

• Journal of Korea Multimedia Society
• /
• v.13 no.7
• /
• pp.991-999
• /
• 2010

In this paper, we propose a fast motion estimation algorithm for video encoding. Conventional fast motion estimation algorithms have a serious problem of low prediction quality in some frames. However, full search based fast algorithms have low computational reduction ratio. In the paper, we propose an algorithm that significantly reduces unnecessary computations, while keeping prediction quality almost similar to that of the full search. The proposed algorithm uses distribution probability of motion vectors and adaptive search patterns and block matching criteria. By taking different search patterns and error criteria of block matching according to distribution probability of motion vectors, we can reduces only unnecessary computations efficiently. Our algorithm takes only 20~30% in computational amount and has decreased prediction quality about 0~0.02dB compared with the fast full search of the H.264 reference software. Our algorithm will be useful to real-time video coding applications using MPEG-2 or MPEG-4 AVC standards.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.07a
• /
• pp.231-233
• /
• 2012

HEVC 비디오 코덱에서는 인터 예측을 수행할 때 고정된 지수 골룸 코드를 사용하여 차분 움직임 벡터를 부호화한다. 그러나 고정된 Exp-Golomb 코드를 사용하게 되면 영상의 움직임을 고려하지 않고 영상의 국지적인 특성을 반영하는데 어려움이 있다. 본 논문에서는 현재 블록의 MVP와 예측된 MV에 따라 적응적인 Exp-Golomb 코드를 결정하는 방법을 제안한다. 현재 블록의 MVP에 따라 현재 MV를 예측하는 MV모델링을 통하여 Exp-Golomb 코드를 결정한다. HEVC의 참조소프트웨어인 HM6.0을 이용하여 실험한 결과, Random Access 부호화 구조에서는 평균적으로 약 0.9%의 성능 향상을 얻을 수 있었으며, Low Delay 부호화 구조에서는 약 0.6%의 BD-rate의 감소를 확인할 수 있었다.