Results 71 to 80 of about 28,524 (229)
Shock and Vibration, 2019 The identification of operational modal parameters of a wind turbine blade is fundamental for online damage detection. In this paper, we use binocular photogrammetry technology instead of traditional contact sensors to measure the vibration of blade and ...
Wenyun Wang, Xuejun Li, Anhua Chen
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Understanding Stochastic Subspace Identification
, 2006 The data driven Stochastic Subspace Identification techniques is considered to be the most powerful class of the known identification techniques for natural input modal analysis in the time domain. However, the techniques involves several steps of "mysterious mathematics" that is difficult to follow and to understand for people with a classical ...
Brincker, Rune, Andersen, Palle
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Measure‐valued processes for energy markets
Mathematical Finance, Volume 35, Issue 2, Page 520-566, April 2025.Abstract We introduce a framework that allows to employ (non‐negative) measure‐valued processes for energy market modeling, in particular for electricity and gas futures. Interpreting the process' spatial structure as time to maturity, we show how the Heath–Jarrow–Morton approach can be translated to this framework, thus guaranteeing arbitrage free ...
Christa Cuchiero +3 more
wiley +1 more source
LQ decomposition based subspace identification under deterministic type disturbance
Systems Science & Control Engineering, 2017 To overcome the influence from deterministic type load disturbance with unknown dynamics, a bias-eliminated subspace identification method is proposed for consistent estimation.
Shengnan Zhang +3 more
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Improved Stochastic Subspace System Identification for Structural Health Monitoring
Journal of Physics: Conference Series, 2015 Structural health monitoring acquires structural information through numerous sensor measurements. Vibrational measurement data render the dynamic characteristics of structures to be extracted, in particular of the modal properties such as natural frequencies, damping, and mode shapes.
Chia-Ming Chang, Chin-Hsiung Loh
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Inference on the Attractor Space via Functional Approximation
Oxford Bulletin of Economics and Statistics, EarlyView.ABSTRACT This paper discusses semiparametric inference on hypotheses on the cointegration and the attractor spaces for I(1)$$ I(1) $$ linear processes with moderately large cross‐sectional dimension. The approach is based on sample canonical correlations and functional approximation of Brownian motions, and it can be applied both to the whole system ...
Massimo Franchi, Paolo Paruolo
wiley +1 more source
A Systematic Review on Applications of Artificial Intelligence for Obesity Prevention
Obesity Reviews, EarlyView.ABSTRACT This systematic review examines the applications of artificial intelligence (AI) in preventing obesity, addressing a critical public health issue that affects a substantial portion of the population. With obesity rates rising alarmingly, particularly in the United States, this review synthesizes findings from 46 studies published between 2008 ...
Atefehsadat Haghighathoseini +4 more
wiley +1 more source
Online Intelligent Identification of Modal Parameters for Large Cable-Stayed Bridges
Shock and Vibration, 2020 Realizing online intelligent identification of bridge modal parameters requires not only the adaptive decomposition of structural response signals but also the enforcement of the automatic identification of modal parameters. Therefore, in this paper, the
Peng Wen +4 more
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A Genetic Algorithm Procedure for the Automatic Updating of FEM Based on Ambient Vibration Tests
Sensors, 2020 The dynamic identification of the modal parameters of a structure, in order to gain control of its functionality under operating conditions, is currently under discussion from a scientific and technical point of views.
Francesca Bianconi +3 more
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Informed Dictionary‐Guided Monte Carlo Inversion for Robust and Reproducible Multidimensional MRI
Magnetic Resonance in Medicine, Volume 95, Issue 5, Page 2947-2962, May 2026.ABSTRACT Purpose To develop a robust and efficient multidimensional MRI (MD‐MRI) data processing framework for accurately estimating joint frequency‐dependent diffusion‐relaxation distributions, while overcoming computational limitations and noise instability inherent to Monte Carlo (MC) inversion.
Joon Sik Park +3 more
wiley +1 more source