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 784 for “"State-space"”.
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State-space models for stream networks
… throughout the stream network, we propose a state-space model to describe the spatial dependence in this tree-like structure with ordering based on flow. Developing a state-space formulation permits the use of the well known Kalman recursions. Variations of the Kalman Filter and Smoother are …
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A state space model for inflation
… when prior knowledge of the initial parameter state is assumed known thus Bayesian analysis is applied and that obtained using classical approach.
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Ensemble filtering for state space models
The state space model has been widely used in various fields including economics, finance, bioinformatics, oceanography, and tomography. The goal of the filtering problem is to find the posterior distribution of the hidden state given the current and past observations. The first part of my thesis …
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Latent state space models for prediction
… model. The new extension is termed as the Latent State Space Copula Model. In the novel Latent State Space Copula Modelthe ECG, ABP signals are considered to be correlated and are modeled using a bivariate Gaussian copula with Weibull marginals generated by a hidden state. We assume that there are …
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State-space formulation for structure dynamics
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1996.
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Limiting controls in vector state space systems
… constraints. Focusing mostly on linear vector state space systems, we investigate how limits on the frequency of system actuation affect control policies. Two types of actuation constraints are considered. The first places a limit on the total number of actuations, while the second places a …
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A state-space approach to dynamic tomography
… development of the dissertation. The proposed state-space formulation provides a natural and general statistical framework for the systematic tomographic reconstruction of dynamic objects when faced with inevitable measurement and modeling uncertainties. In addition, the dissertation offers …
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State space models of remote manipulation tasks.
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1968.
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State-space modeling of MEG time series
… problem can be easily formulated as a state-space model (SSM) problem, the high dimension of the resulting state-space makes this approach computationally impractical. In this thesis we use a SSM to characterize from MEG recordings the spatiotemporal dynamics of underlying neural …
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Building a state space for song learning
Song learning circuitry is thought to operate using a unique representation of each moment within each song syllable. Distinct timestamps for each moment in the song have been observed in the premotor cortical nucleus HVC, where neurons burst in sparse sequences. However, such sparse sequences are …
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State space models for isolating neural oscillations
… We propose an alternative approach that uses state space models to represent basic physiological and dynamic principles, whose detailed structure and parameterization are informed by observed data. We find that this method can more accurately represent oscillatory power, effectively separating …
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Evaluating machine-independent metrics for state-space exploration
… heuristic techniques in tools that explore the state spaces of tests for such programs. To empirically evaluate these techniques, researchers apply them on subject programs, capture a set of metrics, and compare these metrics to provide some measure of the techniques’ effectiveness. From a …
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Enhancing deep state space models for complex applications
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01
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On maximum likelihood identification of state space models
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1979.
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State-space multitaper spectrogram algorithms : theory and applications
I present the state-space multitaper approach for analyzing non-stationary time series. Nonstationary time series are commonly divided into small time windows for analysis, but existing methods lose predictive power by analyzing each window independently, even though nearby windows have similar …
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Ecosystem Models in a Bayesian State Space Framework
… mechanistic process models used into statistical state space frameworks for environmental prediction and forecasting applications. In this study, I focus on Bayesian State Space Models (SSMs) for modeling the temporal dynamics of carbon in terrestrial ecosystems. In Chapter 1, I provide an …
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Efficient state space exploration of reactive object-oriented programs
In dieser Arbeit werden neue Ansätze zur Zustandsexploration von eingebetteten C++ Programmen vorgestellt, die eine effiziente Suche nach Zuständen mit bestimmten Eigenschaften erlauben. Um eine einheitliche Behandlung von eingebetteten C++ Programmen zu ermöglichen, wird zunächst eine Erweiterung …
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Decentralized state-space controller design of a large PHWR
… into three partitions containing 20, 27, and 25 states each. Reduced order sub-systems were thus created to produce optimal decentralized controllers. An optimal centralized controller was created to compare both approaches. The decentralized versus centralized controllers’ system responses were …
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