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.
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Showing 1 to 20 of 52 for “"model identification"”.
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Model identification with application to building control and fault detection
… cost of one more non-linear term. The resulting model coefficients are valid for predicting heat rate given zone temperature as well as for predicting zone temperature given heat rate. Control. Three important control applications involving transient zone thermal response are HVAC curtailment, …
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Multiscale stochastic realization and model identification with applications to large-scale estimation problems
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.
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Essays on Immigrant Mental Health: A Look at Health Reporting, Model Identification, and Policy Changes
… orthogonal polynomial parameterization in the model, results suggest that period effects are insignificant and thus do not play a role in explaining immigrant mental health. Furthermore, mental health appears to decline the longer immigrants remain in Canada in the survey data, but not in the …
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New progress in hot-spots detection, partial-differential-equation-based model identification and statistical computation
… partial-differential-equation-based (PDE-based) model identification, and (3) optimization in the Least Absolute Shrinkage and Selection Operator (Lasso) type problem. In this thesis, we have four main works. Chapter 1 and Chapter 2 fall in the first area, i.e., hot-spots detection in …
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Dynamic substructuring of complex hybrid systems based on time-integration, model reduction and model identification techniques
… a consistent degradation between PSs and NSs via model updating techniques; ii) handling PSs characterized by several internal DoFs with a reduced number of interface actuation points; iii) improving the computational efficiency in the case of complex NSs via partitioned time integrators. An old …
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UAS Model Identification and Simulation to Support In-Flight Testing of Discrete Adaptive Fault-Tolerant Control Laws
… research illustrates the results of systems identification that is performed using DATCOM followed by the flight test data. This data is acquired from conducting an intensive flight testings program of a fixed-wing UAS to determine the state-space model of the aircraft. A discrete state-space …
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Automated symbolic model identification for nonlinear dynamical systems from time-series data with limited sampling frequency and precision
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-12-01
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Exploring the impact of polygenes on genetic inheritance model identification, with application to Familial Colorectal Cancer Type X (FCCTX)
… on identifying the factors that enable correct identification of genetic inheritance models. Exploring this topic involved complex segregation analysis on real FCCTX cancer registry data, then on simulated data (based on the real data characteristics) to determine what caused the model to be …
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Stochastic realization theory for exact and approximate multiscale models
… independence structure possessed by multiscale models and demonstrates that such an analysis provides important insight into the multiscale stochastic realization problem. Multiscale models constitute a broad class of probabilistic models which includes the well--known subclass of multiscale …
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Control Relevant Identification of Sheet and Film Processes
… the difficult and interesting control relevant identification problems existing in large scale processes. Existing techniques for model identification require substantially more input-output data than are typically available for these processes, and do not inform the control engineer on how to …
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Detecting Brain Effective Connectivity with Supervised and Bayesian Methods
… that is based on the multivariate autoregressive model, where we face the problem of model identification. For this purpose, we present a new Bayesian method for linear model identification and we explore its capability of modeling the sparsity structure of the signals. As a second contribution, …
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Internal multiscale autoregressive processes, stochastic realization, and covariance extension
The focus of this thesis is on the identification of multiscale autoregressive (MAR) models for stochastic processes from second-order statistical characterizations. The class of MAR processes constitutes a rich and powerful stochastic modeling framework that admits efficient statistical inference …
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Simulation and Optimization of Batch Crystallization Processes
… has motivated great interest toward quickly modeling and simulating the crystallization processes, as well as the development of optimal control strategies for these processes. Here an iterative procedure is developed for the robust optimal identification and control of batch and semibatch …
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Identification and control of an automated off highway agricultural vehicle
… to this problem is to first perform a tractor model identification, and then use a pole placement technique to place the closed loop dominant poles in their desired locations. One of the most difficult aspects of designing a controller for vehicle guidance is arriving at a good model of vehicle …
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Computational Methods for the Assessment of Brain Connectivity in Visuo-Motor Integration Processes
The identification of the networks connecting different brain areas, as well as the understanding of their role in executing complex behavioral tasks, are crucial issues in cognitive neurosciences. In this context, several time series analysis approaches are available for the investigation of brain …
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Conditional Quantile Estimation With Ordinal Data
… the proposed ordinal quantile regression model, such as the model identification, interpretation of estimators from the model, estimation of probabilities, are addressed. The simulated annealing algorithm is used for the optimization. The proposed ordinal quantile regression method is …
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Monotonicity aspects of linguistic fuzzy models
Their interpretable model structure sets linguistic fuzzy m models apart from other modelling techniques and is considered their greatest asset. Therefore, in the identification process of a linguistic fuzzy model, the interpretability of the model should be safeguarded or at least be balanced …
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Advanced Methods for Image Forensics: First Quantization Estimation and Document Authentication
… task specifici: il primo è relativo alla Camera Model Identification (CMI) con l'obiettivo di identificare la tabella di quantizzazione utilizzata durante la prima compressione JPEG; il secondo sfrutta l'immagine come digitalizzazione di un vero foglio di carta per estrarre un'impronta digitale …
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SAMoSSA: Multivariate Singular Spectrum Analysiswith Stochastic Autoregressive Noise
… mSSA; (ii) we extend the analysis of AR process identification in the presence of arbitrary bounded perturbations; (iii) we characterize the out-of-sample or forecasting error, as opposed to solely considering model identification. Through representative empirical studies, we validate the …
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Is the most likely model likely to be the correct model?
… 2-dimensional dependencies of a deterministic model can be correctly recovered via hypothesis-enumeration and Bayesian selection for a linear sequence, and what the degree of 'ignorance' or 'uncertainty' is that Bayesian selection can tolerate concerning the properties of the model and data. …
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