• 호남수학학술지
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• 제38권3호
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• pp.613-623
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• 2016

As a generalization of the Fourier transform, the fractional Fourier transform plays an important role both in theory and in applications of signal processing. We present a new approach to reach a uniform sampling theorem in the shift-invariant spaces associated with the fractional Fourier transform domain.

• 조명전기설비학회논문지
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• 제29권9호
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• pp.14-22
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• 2015

TIn this paper, a centering method for an unfocused input character using the spherical domain system and the centering character to use the shift invariant feature for the recognition system is proposed. A system for recognition is implemented using the centroid method with coordinate average values, and the results of an above 78.14% average differential ratio for the character features were obtained. It is possible to extract the shift invariant feature using spherical transformation similar to the human eyeball. The proposed method, which is feature extraction using spherical coordinate transform and transformed extracted data, makes it possible to move the character to the center position of the input plane. Both digital and optical technologies are mixed using a spherical coordinate similar to the 3 dimensional human eyeball for the 2 dimensional plane format. In this paper, a centering character feature using the spherical domain is proposed for character recognition, and possibilities for the recognized possible character shape as well as calculating the differential ratio of the centered character using a centroid method are suggested.

• Journal of information and communication convergence engineering
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• 제21권2호
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• pp.139-144
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• 2023

Engineers prefer deep neural networks (DNNs) for solving computer vision problems. However, DNNs pose two major problems. First, neural networks require large amounts of well-labeled data for training. Second, the covariate shift problem is common in computer vision problems. Domain adaptation has been proposed to mitigate this problem. Recent work on adversarial-learning-based unsupervised domain adaptation (UDA) has explained transferability and enabled the model to learn robust features. Despite this advantage, current methods do not guarantee the distinguishability of the latent space unless they consider class-aware information of the target domain. Furthermore, source and target examples alone cannot efficiently extract domain-invariant features from the encoded spaces. To alleviate the problems of existing UDA methods, we propose the mixup regularization in adversarial discriminative domain adaptation (ADDA) method. We validated the effectiveness and generality of the proposed method by performing experiments under three adaptation scenarios: MNIST to USPS, SVHN to MNIST, and MNIST to MNIST-M.

• 한국군사과학기술학회지
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• 제24권4호
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• pp.382-391
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• 2021

Unsupervised domain adaptation often gives impressive solutions to handle domain shift of data. Most of current approaches assume that unlabeled target data to train is abundant. This assumption is not always true in practices. To tackle this issue, we propose a general solution to solve the domain gap minimization problem without any target data. Our method consists of two regularization steps. The first step is a pixel regularization by arbitrary style transfer. Recently, some methods bring style transfer algorithms to domain adaptation and domain generalization process. They use style transfer algorithms to remove texture bias in source domain data. We also use style transfer algorithms for removing texture bias, but our method depends on neither domain adaptation nor domain generalization paradigm. The second regularization step is a feature regularization by feature alignment. Adding a feature alignment loss term to the model loss, the model learns domain invariant representation more efficiently. We evaluate our regularization methods from several experiments both on small dataset and large dataset. From the experiments, we show that our model can learn domain invariant representation as much as unsupervised domain adaptation methods.

• 지능정보연구
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• 제15권4호
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• pp.201-212
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• 2009

확산 스펙트럼 방식 워터마킹 기술은 일반적인 공격에 매우 강인한 알고리즘으로 알려져있으나 시간 축 변형 공격에 대해서 만큼은 취약성을 드러내고 있다. 본 연구에서는 확산 스펙트럼 방식 워터마킹 기술의 장점을 살리면서 시간 축 공격에도 강인한 알고리즘을 제안한다. 시간 축 공격은 오디오 신호의 주파수 성분을 변화시키거나 피치성분은 유지하면서 오디오 신호의 길이를 변화시키는 등의 공격을 포함하고 있다. 확산 스펙트럼 방식에 의해서 삽입된 워터마크를 검출하기 위해서는 시간 축 공격의 비율을 정확히 알아야만 한다는 어려움이 있으며, 그 비율을 알기 위해서는 많은 알고리즘의 처리가 필요하고 현실적으로 구현이 불가능한 등의 어려움이 있다. 본 연구에서는 이러한 문제점을 해결하기 위해서 오디오 신호를 시 불변 영역(time-invariant domain)으로 변환하고, 이 영역에서 확산 스펙트럼 방식의 워터마크를 삽입함으로써 확산 스펙트럼 방식의 장점을 유지하고 시간 축 공격에 대해서도 강인한 알고리즘을 제안하였다. 이를 위해서 오디오 신호에 대해 log scale time axis를 사용하고, log scale time axis 신호를 Fourier 변환함으로써 시 불변 영역을 얻을 수 있었다.

• 대한수학회지
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• 제54권3호
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• pp.821-833
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• 2017

We get a result that shows the existence of infinitely many solutions for a class of the elliptic systems involving subcritical Sobolev exponents nonlinear terms with even functionals on the bounded domain with smooth boundary. We get this result by variational method and critical point theory induced from invariant subspaces and invariant functional.

• 제어로봇시스템학회논문지
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• 제6권5호
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• pp.339-344
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• 2000

This paper is concerned with the simplification of complex linear time-invariant systems. A simple technique is suggested using the well-known least squares method in the frequency domain. Given a high-order transfer function in the s- or z-domain, the squared-gain function corresponding to a low-order model is computed by the least squares method. Then, the low-order transfer function is obtained through the factorization. Three examples are given to illustrate the efficiency of the proposed method.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제67차 동계학술대회논문집 31권1호
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• pp.17-18
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• 2023

비지도형 도메인 적응(UDA)에 대한 최근 연구는 도메인 적응에 대한 설명 및 전이 가능한 특징을 풀어 내기 위해 적대적 학습에 의존한다. 그러나 기존 방법에는 대상 도메인의 클래스 인식(class-aware) 정보를 고려하지 않고는 잠재 공간의 구별 가능성을 완전히 보장할 수 없다는 것과 소스 및 대상 도메인의 샘플만으로는 잠재 공간에서 도메인 불변(domain- invariant) 특성을 추출하기에 부족하다는 두 가지 문제가 있다고 알려져 있다. 본 논문에서는 기존 알려진 UDA의 도메인 적응시 발생되는 문제를 해결하기 위해 Adversarial Discriminative Domain Adaptation(ADDA)에서 mixup을 활용해 신경망의 로버스트네스를 향상시키는 것을 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 학술대회지
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• pp.897-899
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• 2004

There is scientific work containing the recurrence method of synthesis the new class of orthogonal circle m-invariant signals: designed effective algorithms of fast-direct computing m-convolution in time domain: engineer methods of design economic scheme of decoders for optimal receiving in aggregate of suggested signal.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.565-568
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• 1996

In this paper, a solution method is proposed to calculate the optimum solution to discrete optimal H$_{.inf}$ control problem for feedback of linear time-invariant system states and disturbance variable. From the results of this study, condition of existence and uniqueness of its solution is that transfer matrix of controlled variable to input variable is left invertible and has no invariant zeros on the unit circle of the z-domain as well as extra geometric conditions given in this paper. Through a numerical example, the noniterative solution method proposed in this paper is illustrated.