Structural health monitoring with non-linear sensor measurements robust to unknown non-stationary input forcing
Bayesian filtering based structural health monitoring algorithms typically assume stationary
white Gaussian noise models to represent an unknown input forcing. However, typical …
white Gaussian noise models to represent an unknown input forcing. However, typical …
A Kriging-based Interacting Particle Kalman Filter for the simultaneous estimation of temperature and emissivity in Infra-Red imaging
T Toullier, J Dumoulin, L Mevel - IFAC-PapersOnLine, 2020 - Elsevier
Temperature estimation through infrared thermography is facing the lack of knowledge of the
observed material's emissivity. The derivation of the physical equations lead to an ill-posed …
observed material's emissivity. The derivation of the physical equations lead to an ill-posed …
A Study on Kernel Size Adaptation for Correntropy-based Learning Algorithms
N Kim - Journal of the Korea Academia-Industrial cooperation …, 2021 - koreascience.kr
The ITL (information theoretic learning) based on the kernel density estimation method that
has successfully been applied to machine learning and signal processing applications has a …
has successfully been applied to machine learning and signal processing applications has a …
[PDF][PDF] 코렌트로피기반학습알고리듬의커널사이즈에관한연구
김남용 - 한국산학기술학회논문지, 2021 - kais99.org
요약 머신 러닝 및 신호처리에 활용되고 있는 정보이론적 학습법 (ITL, information theoretic
learning) 은 커널 사이즈 (σ) 설정이 매우 민감한 어려움을 지닌다. ITL 의 성능지표중 하나인 …
learning) 은 커널 사이즈 (σ) 설정이 매우 민감한 어려움을 지닌다. ITL 의 성능지표중 하나인 …
코렌트로피학습알고리듬을위한오차분산기반커널사이즈조절
김남용 - 한국통신학회논문지, 2021 - dbpia.co.kr
정보이론적 학습법의 한 성능기준인 MCC (maximum correntropy criterion) 은 기울기에서
항상 커널 사이즈 제곱의 역수를 지니며 이것이 MCC 기반 학습 알고리듬을 불안정하게 만든다 …
항상 커널 사이즈 제곱의 역수를 지니며 이것이 MCC 기반 학습 알고리듬을 불안정하게 만든다 …