Search for dissertations about: "Sequential Monte Carlo method"
Showing result 11 - 15 of 23 swedish dissertations containing the words Sequential Monte Carlo method.
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11. Complexity and Error Analysis of Numerical Methods for Wireless Channels, SDE, Random Variables and Quantum Mechanics
Abstract : This thesis consists of the four papers which consider different aspects of stochastic process modeling, error analysis, and minimization of computational cost. In Paper I, we construct a Multipath Fading Channel (MFC) model for wireless channels with noise introduced through scatterers flipping on and off. READ MORE
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12. Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions
Abstract : Data-driven modeling of stochastic nonlinear systems is recognized as a very challenging problem, even when reduced to a parameter estimation problem. A main difficulty is the intractability of the likelihood function, which renders favored estimation methods, such as the maximum likelihood method, analytically intractable. READ MORE
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13. Structure, phase behavior, and dynamics of colloidal systems characterized by strong, short- and moderate-ranged attractions: a computational study
Abstract : Attractions between colloidal particles are often so strong that non-equilibrium behavior results. However, dissolved non-adsorbing polymer can be added to give a weak attraction between particles so that equilibrium phase transitions appear at moderate polymer concentrations. READ MORE
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14. On computational methods for nonlinear estimation
Abstract : The Bayesian approach provides a rather powerful framework for handling nonlinear, as well as linear, estimation problems. We can in fact pose a general solution to the nonlinear estimation problem. However, in the general case there does not exist any closed-form solution and we are forced to use approximate techniques. READ MORE
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15. Rao-Blackwellised particle methods for inference and identification
Abstract : We consider the two related problems of state inference in nonlinear dynamical systems and nonlinear system identification. More precisely, based on noisy observations from some (in general) nonlinear and/or non-Gaussian dynamical system, we seek to estimate the system state as well as possible unknown static parameters of the system. READ MORE