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 17 of 17 for “"observation models"”.
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Simultaneous Estimation and Modeling of State-Space Systems Using Multi-Gaussian Belief Fusion
… belief is developed, followed by application to observation models. Finally, SEAM is generalized to fully nonlinear and non-Gaussian systems. Several parametric studies were performed on simulated experiments in order to assess the various dependencies of the SEAM framework and validate its …
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Wideband Spectrum Sensing and Signal Classification for Autonomous Self-Learning Cognitive Radios
… a mixture of Gaussian and non-Gaussian vector observation models, compared to existing DPMM's with scalar Gaussian observation models. We also develop a sequential DPMM classifier that can be implemented at a low processing cost, making it suitable for real-time operation. Upon identifying the …
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ΜΕΛΕΤΗ ΤΗΣ ΔΟΜΗΣ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΚΑΙ ΒΕΛΤΙΣΤΟΠΟΙΗΣΗ ΤΟΥ ΕΛΛΗΝΙΚΟΥ ΔΙΚΤΥΟΥ ΠΡΩΤΗΣ ΤΑΞΗΣ
… CRITERIA STUDIES ARE CARRIED OUT USING DIFFERENT OBSERVATION MODELS. BEST FITTING ELLIPSOIDS ARE DETERMINED FOR A READJUSTMENT OF THE NETWORK WITH LESS DISTORTIONS WHICH ARE PRESENT IN THE CASE OF REDUCTION ONTO A NON BEST FITTING REFERENCE SURFACE. RELATED TOPICS ARE ALSO TREATED, E.G., THE …
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Knowledge and Ignorance in Reinforcement Learning
… model, the reward function, and the observation model. In this thesis, I present a framework for studying how the state of knowledge or uncertainty of each component affects the Reinforcement Learning process. I focus on the reward function and the observation model, which has …
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Computational imaging with small numbers of photons
… of individual photon detections, which are observations of an inhomogeneous Poisson process, and express a priori scene constraints for the specific imaging problem. Each yields an inverse problem that can be accurately solved using novel variations on sparse signal pursuit methods and …
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Remote Operator Blended Intelligence System for Environmental Navigation and Discernment (RobiSEND)
… and human, for system integration purposes. Observation models relevant to both human and robotic collaborators are tracked through a boundary based approach deemed AIM-SHIFT. A system is developed to classify the semantic and functional relevance of an observation model to local search …
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Probabilistic modeling of planar pushing
… each sample through the dynamic system and observation models. Effective sampling and accurate probabilistic propagation are possible by relying on the GP form of the system, and a Gaussian mixture form of the belief. In this thesis we show that GP-SUM outperforms several GP-Bayes and …
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An Observation Framework for Recognising Learning Evidence in 3D Collaborative Virtual Environments
… computational framework, and a number of virtual observation models, for classifying learning evidence in immersive environments – and then maps all these elements to an appropriate learning design. In order to implement the computational framework required, the research includes the construction …
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Applications of low-rank matrix recovery methods in computer vision
… analysis that extends existing results to new observation models. Low-rank matrix approximations are a popular tool in data analysis. The well-known Principal Component Analysis (PCA) algorithm is a good example. Recently, it was shown that low-rank matrices can be recovered exactly from …
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Learning-Based Methods for Spacecraft Dynamics Modeling, Filtering, and Predictive Control
… with a set of parameters that are estimated from observations of effective spacecraft dynamics. Without extensive a priori knowledge of the system under study, however, it can be difficult to identify a parametric model structure that accurately captures the dynamics of the system. In this work, …
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Student perceptions of skills learned in undergraduate applied trumpet lessons
… body of research with regard to evaluation, observation, models, and the student-teacher relationship within the applied lesson is developing, little research regarding student perceptions of the applied lesson has been conducted. This warrants research because a student’s perceptions—formed, …
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A Bayesian latent time-series model for switching temporal interaction analysis
… are inferred from noisy and possibly missing observations of these signals. We propose reasoning over posterior distribution of these latent variables as a means of combating and characterizing uncertainty. This approach also allows for answering a variety of questions probabilistically, which …
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High dimensional information processing
… to estimate the sparsity pattern of β given the observation vector y and the measurement matrix X. First, we derive a non-asymptotic upper bound on the probability that a specific wrong sparsity pattern is identified by the maximum-likelihood estimator. We find that this probability depends …
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Feedback particle filter and its applications
… of nonlinearities, not only in the signal models but also in the observation models. For such cases, Kalman filters are known to perform poorly. This motivates simulation-based methods to approximate the infinite-dimensional solution of the K-S SPDE. One popular approach is the particle …
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Managing heterogeneous resources for dynamic energy-efficient sensing
… but at the expense of degraded signal fidelity. Observation models are learned from data for the sensing actions developed in this thesis. The procedure for mapping the problem to a POMDP to generate optimal scheduling policies is demonstrated, and our approach to system design is validated by …
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Neuromorphic control of dynamic systems
… system and the discrete-event signal change observation model, to a desired set-point. Moreover, the set of thresholds (sufficient conditions) for the given system to fulfill the prescribed control task is provided. The proposed controller is then extended to handle the case of noise in both …
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Reduced Receivers for Faster-than-Nyquist Signaling and General Linear Channels
… full-complexity equalizer is identical for both models, the internal metric calculations are in general different. Hence, suboptimum methods need not produce the same final output. Additionally, new models working in between the two extremes are proposed and evaluated. Note that the choice of …