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 algorithms"”.
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Stochastic Algorithms in Riemannian Manifolds and Adaptive Networks
The combination of adaptive network algorithms and stochastic geometric dynamics has the potential to make a large impact in distributed control and signal processing applications. However, both literatures contain fundamental unsolved problems. The thesis is thus in two main parts. In part I, we …
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Adiabatic processes, noise, and stochastic algorithms for quantum computing and quantum simulation
… new possibilities for developing useful quantum algorithms and explaining complex many-body physics. The advantages of quantum computation have been demonstrated in a small range of subjects, but the potential applications of quantum algorithms for solving complex classical problems are still …
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Knowledge bases and stochastic algorithms for mining biological data: applications on A-to-I RNA editing and RNAi
Fino alla seconda metà del Novecento, il rapporto tra la Biologia e l Informatica era molto flebile e i dati venivano generalmente raccolti su materiali deperibili come la carta e stipati in schedari. Questa situazione è cambiata grazie all avvento della Bioinformatica, un campo relativamente …
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Particles methods for kinetic equations in plasma physics, collective behaviors and optimization.
… of the density function, and, by introducing stochasticity, they are able to capture the natural property of the system such as randomness and uncertainties. They can also be suitable to solve the issue of high dimensionality related to deterministic schemes and to substantially reduce the …
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A hybrid algorithm for the simulation of biochemical reactions and diffusion
… particle numbers: Small particle numbers require stochastic algorithms, whereas intermediate and large particle numbers can only be treated by computationally more efficient, though perhaps less exact modeling. To address this problem, I developed the COntrollable Approximative STochastic …
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Improving Results of Differential Evolution Algorithm
… cases, engineers and researchers have to rely on algorithms and techniques that can find sub-optimal solutions to these problems. One of the most dependable algorithms for numerical optimisation problems is Differential Evolution (DE). Since its introduction in the mid 1990’s, DE has been on the …
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Fine-scale modelling of rain fields for radio network simulation
… Radar Interference Experiment (CRIE). Numerical algorithms have been developed to interpolate one, two and three dimensional (1D, 2D and 3D) rain rate fields to a finer sampling interval. A series of radar derived rain maps, with a 10 minute sample period, are interpolated to 10 seconds. …
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Analyzing intentions from big data traces of human activities
… settings and focus on developing lightweight stochastic algorithms as solvers to the large-scale convex optimization problems with theoretical guarantees. For optimizing strongly convex objectives, we design an accelerated stochastic block coordinate descent method with optimal sampling; for …
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Diagrammatic many-body methods for anharmonic molecular vibrational properties
… methods are formulated in both deterministic algorithms which rely on the computation of a large number of anharmonic force constants, and stochastic algorithms which require no stored representation of the PES. This is a significant advance because the computation and storage of the PES is a …
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Complexity in physical, living and mathematical systems
… such as Social systems, Ecology, Networks, Stochastic Algorithms or Mathematical sequences. It also proposes in a second place some new methods and methodologies for Complex systems analysis. Some material is based on seven published papers and two preprints under review whose references can …
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3-D modeling of shallow-water carbonate systems : a scale-dependent approach based on quantitative outcrop studies
… study, the evaluation of three commonly used algorithms Truncated Gaussian Simulation (TGSim), Sequential Indicator Simulation (SISim), and Indicator Kriging (IK), were performed for the first time using visual and quantitative comparisons on an ideally suited carbonate outcrop. The results …