# chapter\_16

- [선형변환과 정규 직교 대각화(Orthogonal Diagonalization)](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1601.md)
- [특이값분해(SVD)의 기본 이해](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1602.md)
- [SVD의 기하학적 의미(회전·축척)](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1603.md)
- [축소(SVD)와 데이터 차원 축소(PCA)](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1604.md)
- [잡음 제거(Denoising)와 압축(Compression)](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1605.md)
- [Moore-Penrose 역행렬의 계산](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1606.md)
- [전처리(Preconditioning)와 Lanczos 알고리즘](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1607.md)
- [사영(Projections)과 랭크 감소(Rank Reduction)](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1608.md)
- [고차원 행렬에서의 근사 랭크(Approximate Rank)](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1609.md)
- [정규 방정식과 최소제곱해](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1610.md)
- [이미지·신호 처리에서의 SVD 활용](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1611.md)
- [빅데이터 분석과 병렬 SVD 알고리즘](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1612.md)
- [낮은 랭크(Low-Rank) 근사의 오차 해석](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1613.md)
- [확장 SVD 기법(RSVD, TSVD 등)](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1614.md)
- [행렬 분해 기반 추천 시스템과 다양한 응용](/booil-jung/docs/math/introductions_to_numerical_analysis/chapter_16/1615.md)