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 10 of 10 for “"Unknown Systems"”.
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Learning Stabilizing Controllers for High-dimensional Unknown Systems and Networked Dynamical Systems
… is a fundamental challenge in autonomous systems, particularly for high-dimensional, nonlinear systems that cannot be accurately modeled using differential equations because of the scalability and model transparency, and large-scale networked dynamical systems because of scalability and …
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METHODS COMPARISON ON FLOW MODEL CONSTRUCTION AND PARAMETER ESTIMATION
Knowing the equation of an unknown dynamical system is essential when trying to apply optimal control. Sometimes researchers do not have a comprehensive knowledge to a nonlinear system. The unknown part might be the function representing the relation between states (e.g. transfer function), or key …
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Efficient data collection strategies for rapid learning in physical environments
With the ubiquity of intelligent systems capable of sensing, inferring and acting upon their surroundings, it becomes critical to learn rapidly about unknown systems or environments. However, obtaining empirical data is often costly and involves setting up time consuming experiments or deploying …
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Classification of second-order conformally-superintegrable systems
… last half century the study of superintegrable systems has established itself as an interesting subject with connections to some of the earliest known dynamical systems in mathematical-physics. Systems with constants second-order in the momenta have been particularly well studied in recent …
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Reduced-order Adaptive Output Predictor for a Class of Uncertain Dynamical Systems: Application to EEG-Based Control of Working Memory
… output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a reduced-order adaptive output-predictor scheme based on modal reduction and Lyapunov's method. Moreover, the credibility of the proposed reduced-order adaptive …
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Machine Learning Methods for Decision Making Inference in Healthcare
… 5, I extend a previously developed dynamic systems inference method (Manifold Approximated Gaussian Process Inference) to situations with completely unknown systems dynamics, with applications in system biology and other scientific areas.
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Structural Chemistry of Silicon Phthalocyanines
… and so forth. Both experimentally known and unknown systems are targets in this part. Studies of the hexacoordination and macrocycle effects in the silicon phthalocyanines have revealed distinguishable bond features. Subphthalocyanines incorporating various central atoms have been explored …
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Criteria for evaluating model deficiency for groundwater models and the effects of eliminating deficient models on multi-model analysis using AICC, KIC, AIC, and BIC
… the strength of evidence that they represent an unknown system using different Information Criteria (IC) equations. IC equations are designed to assess the likelihood that a model in a set of models represents the true but unknown system. IC equations do not include a component which identifies a …
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Control of large-scale structures with large uncertainties
… but recently, passive energy dissipation systems have gained popularity. Semi-active and active energy dissipation systems have been shown to outperform purely passive systems, but they are not yet widely accepted in the construction and structural engineering fields. Several factors are …
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Symmetry in Crystal Structure Prediction
… now possible to explore the energy landscapes of unknown systems and predict stable phases with confidence. Having determined the structure of a material, many useful material properties, such as hardness, ionic conductivity and optical absorption spectra can then be calculated in a routine …