[Linear algebra]
1.[Linear algebra] 대각화 | 대각화란, 대각화 가능한 조건은 무엇일까? (1)
Diagonalizable | Eigenvalues, Eigenvectors
2.[Linear algebra] 대각화 | 대각화란, 대각화 가능한 조건은 무엇일까? (2)
대각화 가능의 여러 필요충분조건들.
3.[Linear algebra] 케일리-해밀턴 정리 (1)
T-invariant subspace | T-cyclic subspace | Some definition and examples | Theorem
4.[Linear algebra] 케일리-해밀턴 정리 (2)
Cayley-Hamilton theorem | relation: Characteristic polynomial of T-invariant subspace | relation: Matrix representation of T-invariant subspace
5.[Linear algebra] 행렬의 극한과 마르코프 연쇄 (1)
Matrix limits | 행렬 거듭제곱의 수렴 조건 | Stochastic process | Markov process
6.[Linear algebra] 행렬의 극한과 마르코프 연쇄 (2)
Gershgorin Circle Theorem | Some identity in regular transition matrix | probability vector (fixed vector, stationary vector) | Hardy-Weinberg law
7.[Linear algebra] 내적공간 (1)
inner product | inner product space | norm | orthogonal | orthonormal | pythagorean theorem | parellelogram law
8.[Linear algebra] 내적공간 (2)
orthonormal basis | Gram-Schmidt process | Orthogonal complement | normed space (parallelogram law) metric space (homogeneous, translation invariant)
9.[Linear algebra] 수반연산자 (The Adjoint of linear operator)
the adjoint operator | least squares approximation
10.[Linear algebra] 유니터리 대각화 (1)
normal, self-adjoint operator | unitary, orthogonal operator | rotation, reflection matrix
11.[Linear algebra] 유니터리 대각화 (2)
문제 풀이 | unitarily (orthogonally) equivalent | unitarily (orthogonally) diagonalizable | unitary, orthogonal matrix | normal, symmetric association
12.[Linear algebra] 유니터리 대각화 (3)
orthogonal operators on R2 are rotation and reflections | Rigid Motion 재해석 | 3차원상에서 회전의 행렬 표현 | Conic Section