• 인지과학
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• 제19권1호
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• pp.75-88
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• 2008

시각 장면은 중복적인 정보가 많이 포함되어 있다. 우리의 시각체계는 다양하고 중복적인 정보를 처리하기 위해 뇌 용적을 늘이기보다는 들어오는 외부 정보를 요약한다. 유사한 형태의 다양한 정보가 시각체계에 주어지면 시각체계는 정보의 통계적 특성을 추출해 낸다. 이런 통계적 표상의 대표적 형태가 바로 평균 표상이다. 평균 표상의 한 예로 시각 체계에서 계산해 내는 유사한 여러 크기들의 평균 크기를 들 수 있다. 평균 표상은 빠르고 정확하며 비교적 오랜 시간 지속되는 표상이고 평균 표상의 처리과정 또한 병렬적인 처리과정이다. 하지만 지금까지의 통계 표상에 관한 연구는 행동측정방법에 의한 연구였다. 따라서 본 연구는 기능적 자기 공명 영상 기법을 사용하여 통계 표상에 관한 신경기제를 찾고자 하였다. 사전 연구 결과들에 따르면 특정 자극을 연속하여 제시하였을 때 특정 자극을 담당하는 영역에서 자기 공명 영상 신호가 감소함을 알 수 있다. 본 연구에서는 이 반복 감소 현상을 사용하여 원들의 평균이 동일한 자극을 제시하였을 때 우측 후두 영역에서 유의미하게 자기 공명 영상 신호가 감소하는 것을 발견하였다. 이것은 우측 후두 영역이 시각자극에 대한 평균 표상을 처리하는 영역일 수 있음을 시사한다.

• 한국통신학회논문지
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• 제34권1C호
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• pp.21-27
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• 2009

지수의 signed digit representation을 사용하여 타입 II 최적정규기저에 의해 결정되는 $GF(2^n)$상의 효율적인 지수승 알고리즘을 제안한다. 제안하는 signed digit representation은 $GF(2^n)$에서 non-adjacent form(NAF)를 사용한다. 일반적으로 signed digit representation은 정규기저가 주어진 경우 사용하기 어렵다. 이는 정규 원소의 역원연산이 상당한 지연시간을 갖기 때문이다. 반면에 signed digit representation은 다항식 기저를 이용한 체에 쉽게 적용가능하다. 하지만 본 논문의 결과는 타입 II 최적정규기저(optimal normal basis, ONB), 라는 특별한 정규 기저가 지수의 signed digit representation을 이용한 효율적인 지수승 연산에 이용될 수 있음을 보인다.

• 대한원격탐사학회지
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• 제21권5호
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• pp.393-404
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• 2005

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.5058-5072
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• 2015

Quaternions have been commonly employed in color image processing, but when the existing pure quaternion representation for color images is used in perceptual hashing, it would degrade the robustness performance since it is sensitive to image manipulations. To improve the robustness in color image perceptual hashing, in this paper a full quaternion representation for color images is proposed by introducing the local image luminance variances. Based on this new representation, a novel Full Quaternion Discrete Cosine Transform (FQDCT)-based hashing is proposed, in which the Quaternion Discrete Cosine Transform (QDCT) is applied to the pseudo-randomly selected regions of the novel full quaternion image to construct two feature matrices. A new hash value in binary is generated from these two matrices. Our experimental results have validated the robustness improvement brought by the proposed full quaternion representation and demonstrated that better performance can be achieved in the proposed FQDCT-based hashing than that in other notable quaternion-based hashing schemes in terms of robustness and discriminability.

• 인지과학
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• 제28권2호
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• pp.111-131
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• 2017

연결주의 모델은 계산주의적 관점에서 언어 처리를 연구하는 한 가지 접근법이다. 그리고 연결주의 모델 연구를 진행하는데 있어서 표상(representation)을 구축하는 것은, 모델의 학습 수준 및 수행 능력을 결정한다는 점에서 모델의 구조를 만드는 것만큼이나 중요한 일이다. 연결주의 모델은 크게 지역 표상(localist representation)과 분산 표상(distributed representation)이라는 두 가지 서로 다른 방식으로 표상을 구축해 왔다. 하지만 종래 연구들에서 사용된 지역 표상은 드문 목표 활성화 값을 갖고 있는 출력층의 유닛이 불활성화 하는 제한점을, 그리고 과거의 분산 표상은 표상된 정보의 불투명성에 의한 결과 확인의 어려움이라는 제한점을 갖고 있었으며 이는 연결주의 모델 연구 전반의 제한점이 되어 왔다. 본 연구는 이와 같은 과거의 표상 구축의 제한점에 대하여, 제한된 볼츠만 머신(restricted Boltzmann machine)이 갖고 있는 특징인 정보의 추상화를 활용하여 지역 표상을 가지고 분산 표상을 유도하는 새로운 방안을 제시하였다. 결과적으로 본 연구가 제안한 방법은 정보의 압축과 분산 표상을 지역 표상으로 역변환하는 방안을 활용하여 종래의 표상 구축 방법이 갖고 있는 문제를 효과적으로 해결함을 보였다.

• Asia pacific journal of information systems
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• 제7권1호
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• pp.85-97
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• 1997

This paper is concerned with knowledge representation schemes best suited for human resource management (HRM) problem domains including human resource planing, selection, placement, compensations, performance evaluation, training and labor-management relations. In order to suggest the scheme we consider two research gods. First, we evaluate and prioritize. The knowledge representation techniques of frames rules, semantic nets and predicate logic that hove been recommended to managerial domains. The combined Analytic Hierarchy Process technique is employed to combine individual judgments effectively between two different expert groups. As a result if we are to select a single knowledge representation technique, a frame representation is best for most HRM domains and to combine frames with others is another choice. Second as a strategy for knowledge representation schemes we show some examples for each damn in terms of labeled semantic nets and two types of rules derived from the semantic nets. We propose nine knowledge components as ontologies. The labeled semantic nets con provide some benefits compared with conventional one. More clearly definea node rode information maces it easy to find the ac information. In the rule sets, the variables are the node of the semantic nets. The consistency of rules is validated by the relationship of the knowledge components.

• 한국정보처리학회논문지
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• 제6권11S호
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• pp.3209-3218
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• 1999

Currently in the Web(World Wide Web) environment, HTML(Hyper Text Markup Language) is used for information representation and exchange. But it is thought that HTML has some constraints in information representation of various kinds because of its limited tag set. And it is considered that combining the HTML, which is used for static information representation in Web environment, with Scripting language, which is usually used for multimedia information representation in a synchronized framework, can be very useful. Consequently we show the general trend of the Scripting language in Web environment and show the possibility of HTML and Scripting language amalgamation for Web service improvement.

• 대한수학회논문집
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• 제35권2호
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• pp.487-497
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• 2020

In this paper, we establish a complex matrix representation of the Clifford algebra Cℓ_p,q. The size of our representation is significantly smaller than the size of the elements in L_p,q(ℝ). Additionally, we give detailed information about the spectrum of the constructed matrix representation.

• 전자공학회지
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• 제12권2호
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• pp.25-32
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• 1985

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3172-3193
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• 2018

Recently, several studies have shown that linear representation based approaches are very effective and efficient for image classification. One of these linear-representation-based approaches is the Collaborative representation (CR) method. The existing algorithms based on CR have two major problems that degrade their classification performance. First problem arises due to the limited number of available training samples. The large variations, caused by illumintion and expression changes, among query and training samples leads to poor classification performance. Second problem occurs when an image is partially noised (contiguous occlusion), as some part of the given image become corrupt the classification performance also degrades. We aim to extend the collaborative representation framework under limited training samples face recognition problem. Our proposed solution will generate virtual samples and intra-class variations from training data to model the variations effectively between query and training samples. For robust classification, the image patches have been utilized to compute representation to address partial occlusion as it leads to more accurate classification results. The proposed method computes representation based on local regions in the images as opposed to CR, which computes representation based on global solution involving entire images. Furthermore, the proposed solution also integrates the locality structure into CR, using Euclidian distance between the query and training samples. Intuitively, if the query sample can be represented by selecting its nearest neighbours, lie on a same linear subspace then the resulting representation will be more discriminate and accurately classify the query sample. Hence our proposed framework model the limited sample face recognition problem into sufficient training samples problem using virtual samples and intra-class variations, generated from training samples that will result in improved classification accuracy as evident from experimental results. Moreover, it compute representation based on local image patches for robust classification and is expected to greatly increase the classification performance for face recognition task.