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 11 of 11 for “"Stochastic filtering"”.
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ADVANCES IN STOCHASTIC ANALYSIS ON SPACES OF MEASURES: KOLMOGOROV EQUATIONS RELATED TO STOCHASTIC FILTERING AND MEAN FIELD OPTIMAL STOPPING
Lo scopo di questa Tesi è di studiare alcuni problemi di analisi stocastica e controllo ottimo stocastico, dove alcune variabili prendono valore in spazi di misure positive e di probabilità. La maggior parte del lavoro è dedicata all'introduzione e allo studio di alcune equazioni di Kolmogorov …
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Leveraged Buyouts, Long Term Relationship and Financial Contracting
… private monitoring in continuous time. I apply stochastic filtering theory to characterize the evolution of players' beliefs, which is difficult to do in discrete time. In the third chapter of my dissertation, I study the connection between financial contracting and staged financing in venture …
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Complex shear modulus reconstruction using ultrasound shear-wave imaging
… modulus reconstruction. A result of this is a stochastic filtering approach that uses a priori information about spatio-temporal dynamics of wave propagation to provide low variance estimates of the complex shear modulus. The stochastic filtering approach is studied both in simulation and …
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Compound Lévy random bridges and credit risky asset pricing
… CLRBs. The second part looks at application of stochastic filtering in the current information based asset pricing framework. First, we formulate credit risky asset pricing in the information-based framework as a filtering problem under incomplete information. We derive the Kalman-Bucy filter in …
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Prognostic modelling for residual useful life prediction
… using condition monitoring information.First, stochastic filtering models are applied for residual useful life prediction, andboth failure and censored data are utilized for model parameterization. Then, three typesof threshold based models are developed, namely an adaptive Brownian motion …
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Probabilistic modeling of planar pushing
… studies the problem of data-driven modeling and stochastic filtering of complex dynamical systems. The main contributions are GP-SUM, a filtering algorithm tailored to systems expressed as Gaussian processes (GP), and the probabilistic modeling of planar pushing by combining input-dependent GPs …
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Quantum recurrent neural networks for filtering
The essence of stochastic filtering is to compute the time-varying probability densityfunction (pdf) for the measurements of the observed system. In this thesis, a filter isdesigned based on the principles of quantum mechanics where the schrodinger waveequation (SWE) plays the key part. This …
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Accuracy bounds for normal-incidence acoustic structure estimation
… based on the Wiener- Levinson algorithm of stochastic filtering theory. (2) The bound is developed for estimation in a continuous medium whose structure (acoustic impedance, for exaiple) parametrized by a set of unknown, non-random coefficients, and for which the reflection response may be …
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Multi-curve frameworks and information-based models
… frequencies. In this framework, a distinct stochastic discount factor is assigned to each tradable term within a given market. This term-cognisant approach is first applied to the deposit market, where a novel argument based on funding-swap duality and a constructed stylised systemic and …
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Duality for nonlinear filtering
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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Simultaneous state and input estimation with applications in vehicle problems
… to the meaning of the covariance matrix in stochastic filtering. We show that the estimation and tracking problems considered here include the Kalman filter and the linear quadratic regulator as special cases. The infinite horizon case is also considered for both the estimation and tracking …