Statistical Damage Classification Under Changing Environmental and Operational Conditions

TL;DR: In this article, a different approach is adopted, and proper orthogonal decomposition is considered, and modes extracted from the decomposition may serve two purposes, namely order reduction by projecting high-dimensional data into a lower-dimensional space and feature extraction by revealing relevant but unexpected structure hidden in the data.

TL;DR: Vehicle system dynamics integration encompasses interdisciplinary challenges innovations in various aspects related to vehicle system/subsystems/components dynamic characteristics, modeling and validation, vehicle dynamics state measurement and estimation, vehicle/chassis control systems, coordination of power management and dynamics/stability control, etc.

TL;DR: Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation.

TL;DR: Robotic materials can enable smart composites that autonomously change their shape, stiffness, or physical appearance in a fully programmable way, extending the functionality of classical “smart materials.”

TL;DR: In this article, a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970 is presented, focusing on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.

TL;DR: Time Series Analysis and Forecasting: principles and practice as mentioned in this paper The Oxford Handbook of Quantitative Methods, Vol. 3, No. 2: Statistical AnalysisTime-Series ForecastingPractical Time-Series AnalysisApplied Bayesian Forecasting and Time Series AnalysisSAS for Forecasting Time SeriesApplied Time Series analysisTime Series analysisElements of Nonlinear Time Series analyses and forecastingTime series analysis and forecasting by Example.

TL;DR: The fundamental principles, basic mechanisms, and formal analyses involved in the development of parallel distributed processing (PDP) systems are presented in individual chapters contributed by leading experts.

TL;DR: It is demonstrated that finite linear combinations of compositions of a fixed, univariate function and a set of affine functionals can uniformly approximate any continuous function ofn real variables with support in the unit hypercube.