Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 7 of 7 for “"Surrogate Data"”.
-
Generalized Volterra-Wiener and surrogate data methods for complex time series analysis
… modern tools for time series analysis including surrogate data and Volterra-Wiener modeling. We describe new algorithms converging the two approaches that provide both a sensitive test for nonlinear dynamics and a noise-robust metric for chaos intensity.
-
Manipulations of spike trains and their impact on synchrony analysis
… recorded in parallel. Techniques to obtain these data are meanwhile available, but advancements are needed in the pre-processing of the large volumes of acquired data and in data analysis techniques. Major issues include extracting the signal of single neurons from the noisy recordings (referred …
-
Complexity Analysis of Physiological Time Series with Applications to Neonatal Sleep Electroencephalogram Signals
… Complexity analysis is applied to two clinical data sets of neonatal sleep Electroencephalography(EEG) time series, to uncover the evolution of signal dynamics and its relationship to neurodevelopment and maturation. A review of the advantages and disadvantages of various complexity measures is …
-
Automated Vocabulary Building for Characterizing and Forecasting Elections using Social Media Analytics
Twitter has become a popular data source in the recent decade and garnered a significant amount of attention as a surrogate data source for many important forecasting problems. Strong correlations have been observed between Twitter indicators and real-world trends spanning elections, stock markets, …
-
Enabling streamlined life cycle assessment : materials-classification derived structured underspecification
… LCA by prioritizing targets of more refined data collection and by implementing the use of underspecified surrogate data within LCI analysis. This thesis concentrates on further developing and improving the streamlining methodology of probabilistic underspecification through refinement of the …
-
Leveraging the capacity of human capital in a product development organization
… DSM for the front end system team through data collection, and interviews with the core engineering group at the company; surrogate data from current production CD vehicles was analyzed. I survey the Ford front end system team to understand the frequency and level of interaction among …
-
Water Quality Control in Distribution Systems: Bayesian Optimization & Physics-Informed Machine Learning
… Using Gaussian Process Regression (GPR) as a surrogate data-driven model, this study systematically investigates the effects of various acquisition functions, such as Expected Improvement (EI), Probability of Improvement (PI), Upper Confidence Bound (UCB), and Entropy Search (ES), along with …