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NTIS 바로가기한국운동역학회지 = Korean journal of sport biomechanics, v.23 no.1, 2013년, pp.53 - 62
The methods of fitting a circle to measured data, geometric fit and algebraic fit, have been studied profoundly in various areas of science. However, they have not been applied exactly to a biomechanics discipline for locating the center of rotation of a human joint. The purpose of this study was to...
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핵심어 | 질문 | 논문에서 추출한 답변 |
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기하적합의 단점은 무엇인가? | 기하적합은 최대우도(maximum likelihood)와 동일한 방법으로 추정값이 편의(bias)되지 않으며 가장 정확한 방법(best fit)으로 일반적으로 여겨지고 있다. 그러나 반복적인 계산을 이용해야하는 비선형식이며 초기값의 선택에 따라 지역최소점(local minima)으로 수렴할 가능성, 그리고 노이즈(noise)가 클 경우 느리게 수렴하는 단점이 있다. 따라서 Delogne(1972)는 근사해(approximation)를 구하는 방법을 개발했는데 이 대수적합은 선형식으로 반복계산 없이 바로 해를 구할 수 있기(closed-form)때문에 아주 간단하다. | |
기하적합은 무엇인가? | , 2001; Al-Sharadqah & Chernov, 2009; Gander, Golub & Strebel, 1994). 기하적합이란 자료와 원의 기하적거리의 제곱을 최소가 되도록 하는 것이며, 이외의 방법을 대수적합이라 하는데 대개 파라미터(parameter)를 이용하여 표현한 대수식의 제곱을 최소가 되게 한다. Piazza et al. | |
원을 자료에 적합시키는 알고리즘은 어떻게 분류할 수 있는가? | 원을 자료에 적합시키는 여러 알고리듬(algorithm)은 위와 같은 다양한 분야에서 서로 독립적으로 개발되어 왔는데 크게 두 가지로 분류할 수 있다. 기하적합(geometric fit)과 대수적합(algebraic fit)이다(Ahn et al., 2001; Al-Sharadqah & Chernov, 2009; Gander, Golub & Strebel, 1994). |
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