"행렬의 크로네커 곱 (Kronecker product)"의 두 판 사이의 차이
Pythagoras0 (토론 | 기여) |
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(사용자 2명의 중간 판 16개는 보이지 않습니다) | |||
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− | + | ==개요== | |
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* 두 행렬의 텐서곱 개념 | * 두 행렬의 텐서곱 개념 | ||
− | * 두 벡터공간 V, W 를 정의역으로 하는 선형사상 A, B 에 대하여, <math>V\otimes W</math> 를 정의역으로 하는 선형사상 <math>A\otimes B</math> 을 정의할 수 있다 | + | * 두 유한차원 벡터공간 V, W 를 정의역으로 하는 선형사상 A, B 에 대하여, <math>V\otimes W</math> 를 정의역으로 하는 선형사상 <math>A\otimes B</math> 을 다음과 같이 정의할 수 있다 |
+ | :<math> | ||
+ | (A\otimes B)(v\otimes w)=A(v)\otimes B(w) | ||
+ | </math> | ||
* <math>A\otimes B</math> 의 행렬표현으로부터 행렬의 크로네커 곱을 얻을 수 있다 | * <math>A\otimes B</math> 의 행렬표현으로부터 행렬의 크로네커 곱을 얻을 수 있다 | ||
+ | * <math>A=(a_{ij})</math>로 두면, <math>A\otimes B=(a_{ij}B)</math> | ||
+ | * <math>C=A\otimes B</math>, <math>\mathbf{i}=(i,i')</math>, <math>\mathbf{j}=(j,j')</math>로 두면, <math>C_{\mathbf{i},\mathbf{j}}=A_{i,j}B_{i',j'}</math> | ||
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− | + | ==예== | |
<math>A=\left( \begin{array}{cc} a_{1,1} & a_{1,2} \\ a_{2,1} & a_{2,2} \end{array} \right)</math> | <math>A=\left( \begin{array}{cc} a_{1,1} & a_{1,2} \\ a_{2,1} & a_{2,2} \end{array} \right)</math> | ||
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<math>A\otimes B=\left( \begin{array}{cccccc} a_{1,1} b_{1,1} & a_{1,1} b_{1,2} & a_{1,1} b_{1,3} & a_{1,2} b_{1,1} & a_{1,2} b_{1,2} & a_{1,2} b_{1,3} \\ a_{1,1} b_{2,1} & a_{1,1} b_{2,2} & a_{1,1} b_{2,3} & a_{1,2} b_{2,1} & a_{1,2} b_{2,2} & a_{1,2} b_{2,3} \\ a_{1,1} b_{3,1} & a_{1,1} b_{3,2} & a_{1,1} b_{3,3} & a_{1,2} b_{3,1} & a_{1,2} b_{3,2} & a_{1,2} b_{3,3} \\ a_{2,1} b_{1,1} & a_{2,1} b_{1,2} & a_{2,1} b_{1,3} & a_{2,2} b_{1,1} & a_{2,2} b_{1,2} & a_{2,2} b_{1,3} \\ a_{2,1} b_{2,1} & a_{2,1} b_{2,2} & a_{2,1} b_{2,3} & a_{2,2} b_{2,1} & a_{2,2} b_{2,2} & a_{2,2} b_{2,3} \\ a_{2,1} b_{3,1} & a_{2,1} b_{3,2} & a_{2,1} b_{3,3} & a_{2,2} b_{3,1} & a_{2,2} b_{3,2} & a_{2,2} b_{3,3} \end{array} \right)</math> | <math>A\otimes B=\left( \begin{array}{cccccc} a_{1,1} b_{1,1} & a_{1,1} b_{1,2} & a_{1,1} b_{1,3} & a_{1,2} b_{1,1} & a_{1,2} b_{1,2} & a_{1,2} b_{1,3} \\ a_{1,1} b_{2,1} & a_{1,1} b_{2,2} & a_{1,1} b_{2,3} & a_{1,2} b_{2,1} & a_{1,2} b_{2,2} & a_{1,2} b_{2,3} \\ a_{1,1} b_{3,1} & a_{1,1} b_{3,2} & a_{1,1} b_{3,3} & a_{1,2} b_{3,1} & a_{1,2} b_{3,2} & a_{1,2} b_{3,3} \\ a_{2,1} b_{1,1} & a_{2,1} b_{1,2} & a_{2,1} b_{1,3} & a_{2,2} b_{1,1} & a_{2,2} b_{1,2} & a_{2,2} b_{1,3} \\ a_{2,1} b_{2,1} & a_{2,1} b_{2,2} & a_{2,1} b_{2,3} & a_{2,2} b_{2,1} & a_{2,2} b_{2,2} & a_{2,2} b_{2,3} \\ a_{2,1} b_{3,1} & a_{2,1} b_{3,2} & a_{2,1} b_{3,3} & a_{2,2} b_{3,1} & a_{2,2} b_{3,2} & a_{2,2} b_{3,3} \end{array} \right)</math> | ||
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<math>v=\left( \begin{array}{c} v_1 \\ v_2 \end{array} \right)</math> | <math>v=\left( \begin{array}{c} v_1 \\ v_2 \end{array} \right)</math> | ||
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<math>v\otimes w= \left( \begin{array}{c} v_1 w_1 \\ v_1 w_2 \\ v_1 w_3 \\ v_2 w_1 \\ v_2 w_2 \\ v_2 w_3 \end{array} \right)</math> | <math>v\otimes w= \left( \begin{array}{c} v_1 w_1 \\ v_1 w_2 \\ v_1 w_3 \\ v_2 w_1 \\ v_2 w_2 \\ v_2 w_3 \end{array} \right)</math> | ||
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<math>Av \otimes Bw = (A\otimes B)( v\otimes w) =\left( \begin{array}{c} v_1 w_1 a_{1,1} b_{1,1}+v_2 w_1 a_{1,2} b_{1,1}+v_1 w_2 a_{1,1} b_{1,2}+v_2 w_2 a_{1,2} b_{1,2}+v_1 w_3 a_{1,1} b_{1,3}+v_2 w_3 a_{1,2} b_{1,3} \\ v_1 w_1 a_{1,1} b_{2,1}+v_2 w_1 a_{1,2} b_{2,1}+v_1 w_2 a_{1,1} b_{2,2}+v_2 w_2 a_{1,2} b_{2,2}+v_1 w_3 a_{1,1} b_{2,3}+v_2 w_3 a_{1,2} b_{2,3} \\ v_1 w_1 a_{1,1} b_{3,1}+v_2 w_1 a_{1,2} b_{3,1}+v_1 w_2 a_{1,1} b_{3,2}+v_2 w_2 a_{1,2} b_{3,2}+v_1 w_3 a_{1,1} b_{3,3}+v_2 w_3 a_{1,2} b_{3,3} \\ v_1 w_1 a_{2,1} b_{1,1}+v_2 w_1 a_{2,2} b_{1,1}+v_1 w_2 a_{2,1} b_{1,2}+v_2 w_2 a_{2,2} b_{1,2}+v_1 w_3 a_{2,1} b_{1,3}+v_2 w_3 a_{2,2} b_{1,3} \\ v_1 w_1 a_{2,1} b_{2,1}+v_2 w_1 a_{2,2} b_{2,1}+v_1 w_2 a_{2,1} b_{2,2}+v_2 w_2 a_{2,2} b_{2,2}+v_1 w_3 a_{2,1} b_{2,3}+v_2 w_3 a_{2,2} b_{2,3} \\ v_1 w_1 a_{2,1} b_{3,1}+v_2 w_1 a_{2,2} b_{3,1}+v_1 w_2 a_{2,1} b_{3,2}+v_2 w_2 a_{2,2} b_{3,2}+v_1 w_3 a_{2,1} b_{3,3}+v_2 w_3 a_{2,2} b_{3,3} \end{array} \right)</math> | <math>Av \otimes Bw = (A\otimes B)( v\otimes w) =\left( \begin{array}{c} v_1 w_1 a_{1,1} b_{1,1}+v_2 w_1 a_{1,2} b_{1,1}+v_1 w_2 a_{1,1} b_{1,2}+v_2 w_2 a_{1,2} b_{1,2}+v_1 w_3 a_{1,1} b_{1,3}+v_2 w_3 a_{1,2} b_{1,3} \\ v_1 w_1 a_{1,1} b_{2,1}+v_2 w_1 a_{1,2} b_{2,1}+v_1 w_2 a_{1,1} b_{2,2}+v_2 w_2 a_{1,2} b_{2,2}+v_1 w_3 a_{1,1} b_{2,3}+v_2 w_3 a_{1,2} b_{2,3} \\ v_1 w_1 a_{1,1} b_{3,1}+v_2 w_1 a_{1,2} b_{3,1}+v_1 w_2 a_{1,1} b_{3,2}+v_2 w_2 a_{1,2} b_{3,2}+v_1 w_3 a_{1,1} b_{3,3}+v_2 w_3 a_{1,2} b_{3,3} \\ v_1 w_1 a_{2,1} b_{1,1}+v_2 w_1 a_{2,2} b_{1,1}+v_1 w_2 a_{2,1} b_{1,2}+v_2 w_2 a_{2,2} b_{1,2}+v_1 w_3 a_{2,1} b_{1,3}+v_2 w_3 a_{2,2} b_{1,3} \\ v_1 w_1 a_{2,1} b_{2,1}+v_2 w_1 a_{2,2} b_{2,1}+v_1 w_2 a_{2,1} b_{2,2}+v_2 w_2 a_{2,2} b_{2,2}+v_1 w_3 a_{2,1} b_{2,3}+v_2 w_3 a_{2,2} b_{2,3} \\ v_1 w_1 a_{2,1} b_{3,1}+v_2 w_1 a_{2,2} b_{3,1}+v_1 w_2 a_{2,1} b_{3,2}+v_2 w_2 a_{2,2} b_{3,2}+v_1 w_3 a_{2,1} b_{3,3}+v_2 w_3 a_{2,2} b_{3,3} \end{array} \right)</math> | ||
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− | + | ==메모== | |
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* Math Overflow http://mathoverflow.net/search?q= | * Math Overflow http://mathoverflow.net/search?q= | ||
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− | + | ==관련된 항목들== | |
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− | + | ==매스매티카 파일 및 계산 리소스== | |
− | * | + | * https://docs.google.com/leaf?id=0B8XXo8Tve1cxZGI2OGMwODEtN2E2OS00Njc1LTgwMjktMTQwNWU5OWUzZmYx&sort=name&layout=list&num=50 |
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− | + | ==사전 형태의 자료== | |
* http://ko.wikipedia.org/wiki/ | * http://ko.wikipedia.org/wiki/ | ||
* http://en.wikipedia.org/wiki/Kronecker_product | * http://en.wikipedia.org/wiki/Kronecker_product | ||
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− | * | + | ==리뷰, 에세이, 강의노트== |
− | + | * Loan, Charles F. Van. “The Ubiquitous Kronecker Product.” Journal of Computational and Applied Mathematics, Numerical Analysis 2000. Vol. III: Linear Algebra, 123, no. 1–2 (November 1, 2000): 85–100. doi:10.1016/S0377-0427(00)00393-9. | |
+ | * Henderson, Harold V., Friedrich Pukelsheim, and Shayle R. Searle. “On the History of the Kronecker Product.” Linear and Multilinear Algebra 14, no. 2 (October 1, 1983): 113–20. doi:10.1080/03081088308817548. | ||
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+ | [[분류:선형대수학]] | ||
− | * | + | ==메타데이터== |
− | + | ===위키데이터=== | |
− | ** | + | * ID : [https://www.wikidata.org/wiki/Q1238125 Q1238125] |
+ | ===Spacy 패턴 목록=== | ||
+ | * [{'LOWER': 'kronecker'}, {'LEMMA': 'product'}] | ||
+ | * [{'LOWER': 'zehfuss'}, {'LEMMA': 'matrix'}] | ||
+ | * [{'LOWER': 'tensor'}, {'LOWER': 'product'}, {'LOWER': 'of'}, {'LEMMA': 'matrix'}] |
2021년 2월 17일 (수) 03:59 기준 최신판
개요
- 두 행렬의 텐서곱 개념
- 두 유한차원 벡터공간 V, W 를 정의역으로 하는 선형사상 A, B 에 대하여, \(V\otimes W\) 를 정의역으로 하는 선형사상 \(A\otimes B\) 을 다음과 같이 정의할 수 있다
\[ (A\otimes B)(v\otimes w)=A(v)\otimes B(w) \]
- \(A\otimes B\) 의 행렬표현으로부터 행렬의 크로네커 곱을 얻을 수 있다
- \(A=(a_{ij})\)로 두면, \(A\otimes B=(a_{ij}B)\)
- \(C=A\otimes B\), \(\mathbf{i}=(i,i')\), \(\mathbf{j}=(j,j')\)로 두면, \(C_{\mathbf{i},\mathbf{j}}=A_{i,j}B_{i',j'}\)
예
\(A=\left( \begin{array}{cc} a_{1,1} & a_{1,2} \\ a_{2,1} & a_{2,2} \end{array} \right)\)
\(B=\left( \begin{array}{ccc} b_{1,1} & b_{1,2} & b_{1,3} \\ b_{2,1} & b_{2,2} & b_{2,3} \\ b_{3,1} & b_{3,2} & b_{3,3} \end{array} \right)\)
\(A\otimes B=\left( \begin{array}{cccccc} a_{1,1} b_{1,1} & a_{1,1} b_{1,2} & a_{1,1} b_{1,3} & a_{1,2} b_{1,1} & a_{1,2} b_{1,2} & a_{1,2} b_{1,3} \\ a_{1,1} b_{2,1} & a_{1,1} b_{2,2} & a_{1,1} b_{2,3} & a_{1,2} b_{2,1} & a_{1,2} b_{2,2} & a_{1,2} b_{2,3} \\ a_{1,1} b_{3,1} & a_{1,1} b_{3,2} & a_{1,1} b_{3,3} & a_{1,2} b_{3,1} & a_{1,2} b_{3,2} & a_{1,2} b_{3,3} \\ a_{2,1} b_{1,1} & a_{2,1} b_{1,2} & a_{2,1} b_{1,3} & a_{2,2} b_{1,1} & a_{2,2} b_{1,2} & a_{2,2} b_{1,3} \\ a_{2,1} b_{2,1} & a_{2,1} b_{2,2} & a_{2,1} b_{2,3} & a_{2,2} b_{2,1} & a_{2,2} b_{2,2} & a_{2,2} b_{2,3} \\ a_{2,1} b_{3,1} & a_{2,1} b_{3,2} & a_{2,1} b_{3,3} & a_{2,2} b_{3,1} & a_{2,2} b_{3,2} & a_{2,2} b_{3,3} \end{array} \right)\)
\(v=\left( \begin{array}{c} v_1 \\ v_2 \end{array} \right)\)
\(w=\left( \begin{array}{c} w_1 \\ w_2 \\ w_3 \end{array} \right)\)
\(v\otimes w= \left( \begin{array}{c} v_1 w_1 \\ v_1 w_2 \\ v_1 w_3 \\ v_2 w_1 \\ v_2 w_2 \\ v_2 w_3 \end{array} \right)\)
\(Av \otimes Bw = (A\otimes B)( v\otimes w) =\left( \begin{array}{c} v_1 w_1 a_{1,1} b_{1,1}+v_2 w_1 a_{1,2} b_{1,1}+v_1 w_2 a_{1,1} b_{1,2}+v_2 w_2 a_{1,2} b_{1,2}+v_1 w_3 a_{1,1} b_{1,3}+v_2 w_3 a_{1,2} b_{1,3} \\ v_1 w_1 a_{1,1} b_{2,1}+v_2 w_1 a_{1,2} b_{2,1}+v_1 w_2 a_{1,1} b_{2,2}+v_2 w_2 a_{1,2} b_{2,2}+v_1 w_3 a_{1,1} b_{2,3}+v_2 w_3 a_{1,2} b_{2,3} \\ v_1 w_1 a_{1,1} b_{3,1}+v_2 w_1 a_{1,2} b_{3,1}+v_1 w_2 a_{1,1} b_{3,2}+v_2 w_2 a_{1,2} b_{3,2}+v_1 w_3 a_{1,1} b_{3,3}+v_2 w_3 a_{1,2} b_{3,3} \\ v_1 w_1 a_{2,1} b_{1,1}+v_2 w_1 a_{2,2} b_{1,1}+v_1 w_2 a_{2,1} b_{1,2}+v_2 w_2 a_{2,2} b_{1,2}+v_1 w_3 a_{2,1} b_{1,3}+v_2 w_3 a_{2,2} b_{1,3} \\ v_1 w_1 a_{2,1} b_{2,1}+v_2 w_1 a_{2,2} b_{2,1}+v_1 w_2 a_{2,1} b_{2,2}+v_2 w_2 a_{2,2} b_{2,2}+v_1 w_3 a_{2,1} b_{2,3}+v_2 w_3 a_{2,2} b_{2,3} \\ v_1 w_1 a_{2,1} b_{3,1}+v_2 w_1 a_{2,2} b_{3,1}+v_1 w_2 a_{2,1} b_{3,2}+v_2 w_2 a_{2,2} b_{3,2}+v_1 w_3 a_{2,1} b_{3,3}+v_2 w_3 a_{2,2} b_{3,3} \end{array} \right)\)
메모
- Math Overflow http://mathoverflow.net/search?q=
관련된 항목들
매스매티카 파일 및 계산 리소스
사전 형태의 자료
리뷰, 에세이, 강의노트
- Loan, Charles F. Van. “The Ubiquitous Kronecker Product.” Journal of Computational and Applied Mathematics, Numerical Analysis 2000. Vol. III: Linear Algebra, 123, no. 1–2 (November 1, 2000): 85–100. doi:10.1016/S0377-0427(00)00393-9.
- Henderson, Harold V., Friedrich Pukelsheim, and Shayle R. Searle. “On the History of the Kronecker Product.” Linear and Multilinear Algebra 14, no. 2 (October 1, 1983): 113–20. doi:10.1080/03081088308817548.
메타데이터
위키데이터
- ID : Q1238125
Spacy 패턴 목록
- [{'LOWER': 'kronecker'}, {'LEMMA': 'product'}]
- [{'LOWER': 'zehfuss'}, {'LEMMA': 'matrix'}]
- [{'LOWER': 'tensor'}, {'LOWER': 'product'}, {'LOWER': 'of'}, {'LEMMA': 'matrix'}]