• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.371-381
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• 2000

In this paper, we describes smoothing spline in nonparametric regression and some asymptotic results for estimates of the regression cofficients in the parametric part were biased on semi parametric regression estimator.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.77-86
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• 2002

This paper proposes a modified Duvall beamformer performing spatial smoothing with spatial interpolation. In the proposed beamformer, virtual array signals are generated by spatial interpolation between each neighbor array elements, then all signals are used to perform spatial smoothing. The proposed beamformer overcomes the loss of degrees of freedom caused by spatial smoothing by forming subarrays with interpolated signals. Mathematical description shows that the proposed beamformer can restore the rank of away covariance matrix. Accordingly, the proposed beamformer can minimize the loss of degrees of freedom. Simulation results show that the proposed beamformer can remove all coherent interferences while conventional beamformers cannot.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.145-146
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• 2021

본 연구에서는 카메라의 촬영 시점에 의해서 발생되는 원근감이 광학 흐름 생성에 어떠한 영향을 주는지 살펴보고 광학 흐름 기반 이상행동 탐지 솔루션의 성능을 고도화하기 위해 기존 광학 흐름 영상으로부터 소실점 기반 가중치 행렬을 계산하여 원근감에 따른 광학 흐름 정도를 평활하는 기법에 대해서 연구한다. 카메라의 뷰포인트에 따라 원근감의 발생 정도나 객체의 크기 및 움직임의 정도가 달라지게 되며, 이는 원본 영상 프레임을 광학 흐름의 크기와 방향성으로 표현하는 영상 변환 네트워크를 가진 생성적 적대 신경망을 학습할 때 정상적인 행동 패턴의 범위를 결정짓는 데 방해가 될 수 있다. 이러한 문제를 해결하기 위하여 데이터셋의 배경으로부터 소실점을 추출하고 원근감에 따라 결정되는 광학 흐름의 크기를 평활하는 기법을 개발하여 기존 모델의 성능과 비교하였으며, 프레임 단위의 정확도 성능이 5.75% 향상된 것으로 확인되었다.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.819-825
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• 2014

In this paper, monaural ambient component extraction algorithm based on nonnegative matrix factorization (NMF) is described. The ambience component extraction algorithm in this paper is developed for audio upmixing system; Recent researches have shown that they can enhance listener envelopment if the extracted ambient signal is applied into the multichannel audio upmixing system. However, the conventional method stores all of the audio signal and processes all at once, so it cannot be applied to streaming system and digital signal processor (DSP) system. In this paper, the ambient component extraction algorithm based on on-line nonnegative matrix factorization is developed and evaluated to solve the problem. As a result of analysis of the processed signal with spectral flatness measures in the experiment, it was shown that the developed system can extract the ambient signal similarly with the conventional batch process system.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.581-594
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• 2016

We introduce innovations state space exponential smoothing models (ISS-ESM) that can analyze time series with multiple seasonal patterns. Especially, in order to control complex structure existing in the multiple patterns, the model equations use a matrix consisting of seasonal updating parameters. It enables us to group the seasonal parameters according to their similarity. Because of the grouped parameters, we can accomplish the principle of parsimony. Further, the ISS-ESM can potentially accommodate any number of multiple seasonal patterns. The models are applied to predict electricity demand in Korea that is observed on hourly basis, and we compare their performance with that of the traditional exponential smoothing methods. It is observed that the ISS-ESM are superior to the traditional methods in terms of the prediction and the interpretability of seasonal patterns.

• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.24-31
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• 1994

In this paper, we study continuous speech recognition of Korean language using acoustic models of word juncture coarticulation. To alleviate the performance degradation due to coarticulation problems, we use context-dependent units that model inter-word transitions in addition to intra-word transitions. In all cases the initial phone of each word has to be specified for each possible final phone of the previous word similarly for the final phone of each word. To improve the robustness of the HMM parameters, the covariance matrix is smoothed. We also use position-dependent units to improve the discriminative power between units. Simulation results show that when the improved models of word juncture coarticulation are used. the recognition performance is considerably improved compared to the baseline system using only intra-word units.