Search for dissertations about: "input constraints"
Showing result 1 - 5 of 173 swedish dissertations containing the words input constraints.
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1. Protein modelling by the zipping and assembly method with limited NMR-derived constraints
Abstract : Molecular dynamics simulations, often combined with simulated annealing, are commonly used when calculating structural models of proteins, e.g. based on NMR experiments. However, one is often faced with limited and, sometimes, insufficient information for determining a well-resolved 3D structure. READ MORE
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2. On Solving String Constraints
Abstract : Software systems are deeply involved in diverse human activities as everyone uses a variety of software systems on a daily basis. It is essential to guarantee that software systems all work correctly. Two popular methods for finding failures of software systems are testing and model checking. READ MORE
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3. Optimal input design for nonlinear dynamical systems : a graph-theory approach
Abstract : Optimal input design concerns the design of an input sequence to maximize the information retrieved from an experiment. The design of the input sequence is performed by optimizing a cost function related to the intended model application. Several approaches to input design have been proposed, with results mainly on linear models. READ MORE
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4. Development and evaluation of methods for control and modelling of multiple-input multiple-output systems
Abstract : In control, a common type of system is the multiple-input multiple-output (MIMO) system, where the same input may affect multiple outputs, or conversely, the same output is affected by multiple inputs. In this thesis two methods for controlling MIMO systems are examined, namely linear quadratic Gaussian (LQG) control and decentralized control, and some of the difficulties associated with them. READ MORE
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5. Estimation and optimal input design in sparse models
Abstract : Sparse parameter estimation is an important aspect of system identification, as it allows for reducing the order of a model, and also some models in system identification inherently exhibit sparsity in their parameters. The accuracy of the estimated sparse model depends directly on the performance of the sparse estimation methods. READ MORE