• 제목/요약/키워드: 2-1 norm

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강인한 역산으로서의 하이브리드 $l^1/l^2$ norm IRLS 방법의 효율적 구현기법 (An Efficient Implementation of Hybrid $l^1/l^2$ Norm IRLS Method as a Robust Inversion)

  • 지준
    • 지구물리와물리탐사
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    • 제10권2호
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    • pp.124-130
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    • 2007
  • 탄성파 역산에 있어서 가장 널리 사용되는 최소자승($l^2$ norm)해는 이상치(outlier)에 매우 민감하게 반응하는 경향이 있다. 이에 반해서 $l^1$ norm을 최소화하는 해는 이상치에 강인한 면을 보이나 일반적으로 좀 더 많은 계산이 필요하다. 반복적가중의 최소자승법(Iteratively reweighted least squares [IRLS] method)을 이용하면 이러한 $l^1$ norm 문제의 근사해(approximate solution)를 효율적으로 구할 수 있다. 본 논문에서는 작은 크기의 잔여분은 $l^2$ norm으로 처리하며, 큰 크기의 잔여분은 $l^1$ norm으로 처리하는 하이브리드 $l^1/l^2$ norm 최소화를 IRLS 방법에 쉽게 적용하는 구현 기법을 소개한다. 소개된 알고리즘은 특이치(singularity)처리를 위한 임계값의 결정에 민감하게 반응하는 기존의 $l^1$ norm IRLS 방법과는 달리 임계값 결정에 상관없이 늘 강인한 역산의 특성을 보여준다.

${\ell}^1/{\ell}^2$ norm IRLS 방법을 사용한 강인한 탄성파자료역산 (Robust inversion of seismic data using ${\ell}^1/{\ell}^2$ norm IRLS method)

  • 지준
    • 한국지구물리탐사학회:학술대회논문집
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    • 한국지구물리탐사학회 2005년도 공동학술대회 논문집
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    • pp.227-232
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    • 2005
  • 탄성파 역산에 있어서 최소자승(${\ell}^2-norm$)해는 큰 오차에 매우 민감하게 반응하는 경향이 있다. 이에 반해서 ${\ell}^p-norm$ ($1{\le}p<2$)을 최소화하는 해는 잡음에 강인한 해를 보이나 보통은 좀 더 많은 계산이 요구된다. 반복적가중의 최소자승법(Iteratively reweighted least squares [IRLS] method)은 이러한 ${\ell}^p-norm$ 문제의 근사해를 효율적으로 구할 수 있도록 해준다. 본 논문에서는 작은 크기의 잔여분은 ${\ell}^2-norm$으로 큰 크기의 잔여분은 ${\ell}^2-norm$으로 적용되는 하이브리드 ${\ell}^1/{\ell}^2$최소화를 IRLS 방법에 쉽게 적용하는 기법을 소개한다. 모의 자료와 실제 현장자료에의 적용결과 큰 잡음이 포함된 경우 최소자승해보다 하이브리드 방법의 경우에 개선된 결과를 보임을 확인할 수 있었다.

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L0 Norm 기반의 LE(Local Effect) 연산자를 이용한 디지털 이미지 위변조 검출 기술 개발 (Development of Digital Image Forgery Detection Method Utilizing LE(Local Effect) Operator based on L0 Norm)

  • 최용수
    • 한국소프트웨어감정평가학회 논문지
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    • 제16권2호
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    • pp.153-162
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    • 2020
  • 디지털 이미지 위조 탐지는 디지털 포렌식 분야에서 매우 중요한 분야 중 하나이다. 기술의 발전을 통해 위조된 이미지가 자연스럽게 바뀜에 따라 이미지 위조를 감지하기 어렵게 만들었다. 본 논문에서는 디지털 이미지에서 복사 붙여넣기 위조에 대한 수동적 위조 검출을 이용한다. 또한, L0 Norm 기반 LE 연산자를 사용해 복사 붙여넣기 위조를 검출함과 동시에 기존에 존재하던 L2, L1 Norm 기반 LE 연산자를 이용한 위조 검출 정확도를 비교하였다. 제안한 하삼각 윈도우를 적용하고 L2, L1 및 L0 Norm 기반 LE 연산자를 통해 BAG 불일치를 검출하고 위조 검출률을 측정하였다. 검출률의 비교에서 제안한 하삼각 윈도우는 기존의 윈도우 필터보다 BAG 불일치 검출에 강인함을 볼 수 있었다. 또한, 하삼각 윈도우를 쓰는 경우 L2, L1, L0 Norm LE 연산으로 갈수록 이미지 위조 검출의 성능이 점점 높게 측정되었다.

lp-norm regularization for impact force identification from highly incomplete measurements

  • Yanan Wang;Baijie Qiao;Jinxin Liu;Junjiang Liu;Xuefeng Chen
    • Smart Structures and Systems
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    • 제34권2호
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    • pp.97-116
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    • 2024
  • The standard l1-norm regularization is recently introduced for impact force identification, but generally underestimates the peak force. Compared to l1-norm regularization, lp-norm (0 ≤ p < 1) regularization, with a nonconvex penalty function, has some promising properties such as enforcing sparsity. In the framework of sparse regularization, if the desired solution is sparse in the time domain or other domains, the under-determined problem with fewer measurements than candidate excitations may obtain the unique solution, i.e., the sparsest solution. Considering the joint sparse structure of impact force in temporal and spatial domains, we propose a general lp-norm (0 ≤ p < 1) regularization methodology for simultaneous identification of the impact location and force time-history from highly incomplete measurements. Firstly, a nonconvex optimization model based on lp-norm penalty is developed for regularizing the highly under-determined problem of impact force identification. Secondly, an iteratively reweighed l1-norm algorithm is introduced to solve such an under-determined and unconditioned regularization model through transforming it into a series of l1-norm regularization problems. Finally, numerical simulation and experimental validation including single-source and two-source cases of impact force identification are conducted on plate structures to evaluate the performance of lp-norm (0 ≤ p < 1) regularization. Both numerical and experimental results demonstrate that the proposed lp-norm regularization method, merely using a single accelerometer, can locate the actual impacts from nine fixed candidate sources and simultaneously reconstruct the impact force time-history; compared to the state-of-the-art l1-norm regularization, lp-norm (0 ≤ p < 1) regularization procures sufficiently sparse and more accurate estimates; although the peak relative error of the identified impact force using lp-norm regularization has a decreasing tendency as p is approaching 0, the results of lp-norm regularization with 0 ≤ p ≤ 1/2 have no significant differences.

대도시 중산층의 주거규범에 관한 연구 - 서울시에 거주하는 주부를 중심으로 - (A Study on the Housing Norm of the Large Cities' Middle Classes - With special reference to the housewives living in Seoul area)

  • 이연복
    • 한국주거학회논문집
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    • 제2권1호
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    • pp.13-34
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    • 1991
  • The main purpose of this study is to examine housing norm of the middle classes, housing norm and normative housing deficits by independent variables(socio - economic variables, family characteristic variable sand housing characteristic variables).There are two major findings of this study as follows :1. In the housing norm, housing space is 99.Om2, the number of rooms is 3.0, housing structure type is apartment, the maintenance cost is 13 thousand won, and housing tenure is home ownership. And housing qualify is classified into 5 dimensions, and neighborhood environment is classified into 3 dimensions.2. This thesis is to conform Morris et aL.(1984)`s hypotheses that cultural norm is homogeneous in culturally unified society and if it appears heterogeneously, It is the subject`s reporting error of the subjects confusing cultural norm with family norm.

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Two Dimensional Slow Feature Discriminant Analysis via L2,1 Norm Minimization for Feature Extraction

  • Gu, Xingjian;Shu, Xiangbo;Ren, Shougang;Xu, Huanliang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권7호
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    • pp.3194-3216
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    • 2018
  • Slow Feature Discriminant Analysis (SFDA) is a supervised feature extraction method inspired by biological mechanism. In this paper, a novel method called Two Dimensional Slow Feature Discriminant Analysis via $L_{2,1}$ norm minimization ($2DSFDA-L_{2,1}$) is proposed. $2DSFDA-L_{2,1}$ integrates $L_{2,1}$ norm regularization and 2D statically uncorrelated constraint to extract discriminant feature. First, $L_{2,1}$ norm regularization can promote the projection matrix row-sparsity, which makes the feature selection and subspace learning simultaneously. Second, uncorrelated features of minimum redundancy are effective for classification. We define 2D statistically uncorrelated model that each row (or column) are independent. Third, we provide a feasible solution by transforming the proposed $L_{2,1}$ nonlinear model into a linear regression type. Additionally, $2DSFDA-L_{2,1}$ is extended to a bilateral projection version called $BSFDA-L_{2,1}$. The advantage of $BSFDA-L_{2,1}$ is that an image can be represented with much less coefficients. Experimental results on three face databases demonstrate that the proposed $2DSFDA-L_{2,1}/BSFDA-L_{2,1}$ can obtain competitive performance.

QUADRATURE ERROR OF THE LOAD VECTOR IN THE FINITE ELEMENT METHOD

  • Kim, Chang-Geun
    • Journal of applied mathematics & informatics
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    • 제5권3호
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    • pp.735-748
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    • 1998
  • We analyze the error in the p version of the of the finite element method when the effect of the quadrature error is taken in the load vector. We briefly study some results on the $H^{1}$ norm error and present some new results for the error in the $L^{2}$ norm. We inves-tigate the quadrature error due to the numerical integration of the right hand side We present theoretical and computational examples showing the sharpness of our results.

디지털 콘텐츠 저작권 침해의 선행요인 연구 : 효능감, 주관적 규범, 학교정책을 중심으로 (A Study on Factors influencing Digital Contents Piracy Focusing on Efficacy, Subjective Norm and School Policy)

  • 권문주;조남형;김태웅
    • 한국IT서비스학회지
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    • 제12권2호
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    • pp.1-12
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    • 2013
  • A new form of software piracy known as digital piracy has taken the spotlight. Lost revenues due to digital piracy could reach 2,500 billion won in year 2010 alone. This paper examines the causal relationships among the attitude toward digital piracy, subjective norm, economic gain, political efficacy, school policy, etc, in a university setting. Results from survey responses indicate that the social norm and economic gain affect the attitude toward digital piracy, and that school policy influences the subjective norm as well as political efficacy. But, contrary to our expectation, political efficacy has been found to have no impact on the social norm and economic gain. Prior learning experiences have been shown to affect economic gain, but not the subjective norm. As a conclusion, the academic and practical implications of these findings are discussed.

심박변이도를 통한 침자극과 스트레스의 상관관계 연구 (A Study on the Relationship with Acupuncture Stimulation and Stress Using Heart Rate Variability)

  • 이승기;박경모;최우진
    • 동의신경정신과학회지
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    • 제15권1호
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    • pp.197-209
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    • 2004
  • Objectives : The purpose of this case-control research was to investigate the effects of acupuncture stimulation on autonomic nervous system for patients with HRV and to find out relationship with anti-stress effects. Methods : The study group consists of 24 patients with self-recognition of stress as the case group, and 20 normal person as the control group by similar age. We measured HRV of case and control groups before acupuncture stimulation, prick acupuncture in Hegu(LI4), Taichong(Liv3), Shenme(H7), Neiguan(P6), Zusanli(S36). After treating for 20 minutes, measurement values of HRV and PSV were compared for pre-acupuncture and post-acupuncture. Results : 1. LF norm, HF norm, LF/HF between the case and control groups were significant different in HRV before acupuncture stimulation in the 1st experiment. 2. HRT, SDNN, SDSD, LF norm, HF norm, and LF/HF of the case group were significant different in HRV after acupuncture stimulation in the 1st experiment. HRT of the case group was significantly different in HRV after acupuncture stimulation in the 1st experiment. 3. LF norm, HF norm, LF/HF of the case group were significant different between the 1st and 2nd experiment in HRV before acupuncture stimulation. 4. LF norm, HF norm, and LF/HF were significant different between the 1st and 2nd experiment in HRV of patients whose symptoms improved. But HRV of patients whose symptoms unimproved didn't show significant difference. Conclusion : The results suggest that acupuncture stimulation is associated with changed activity in the sympathetic and parasympathetic nervous system. Measurement values of HRV is suitable to estimate the activity of automatic nervous system.

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