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 221 for “"Convergence rate"”.
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Does the business cycle matter for convergence testing? Evidence from U.S. commuting zone level data, 1973-2007
… under normal growth periods, regional convergence rate is lower; while during recession-recovery periods, regional convergence rate is higher. This study also found that the overall trend of the convergence rate was decreasing.
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Compressible Convection and Subduction: Kinematic and Dynamic Modeling
… wedge. Plate reconstruction models show that the convergence rate and age of the incoming plate to trench vary with time, which poses a problem for steady-state subduction models. Thus, I consider the time-dependent convergence rate and age of the incoming plate in the kinematic-dynamic subduction …
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A modified experts algorithm : using correlation to speed convergence with very large sets of experts
… it follows at any given stage. As a result, the convergence rate of the algorithm is heavily dependent on the number of experts which it must consider. We adapt this algorithm for use with a very large set of experts. We do this by capitalizing on the fact that when a set of experts is large, …
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Spectral collocation method for compact integral operators
… $ We prove that 1) for integral equations, the convergence</p> <p>rate depends on the smoothness of true solutions $y(t)$. If $y(t)$</p> <p>satisfies condition (R): $\|y^{(k)}\|_{L^\infty[0,T]}\leq</p> <p>ck!R^{-k}$}, we obtain a geometric rate of convergence; if $y(t)$</p> <p>satisfies …
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O método de direções viáveis em duas estapas para programação não-linear e aplicações a programação quadrática
… optimization. It' s stated an assimptotic convergence method for quadratic programming, based on the sarne ideas. As a consequence of the computational implementation, a constrained line-search·procedure is developed. To avoid ili-conditionning and accelerate the convergence rate, new …
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Practical techniques for rapid and reliable real-time adaptive filtering
… extensive simulation examples, to have superior convergence rate and Mean-Squared Error performance over the Data-Reusing LMS algorithm at the same computational cost. A geometric framework which aids in the presentation of the new class of algorithms is developed. This framework also allows a …
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Bregman Augmented Lagrangian Method: Convergence, acceleration, and applications in reinforcement learning
… augmented Lagrangian method (ALM ), whose convergence rate and its relation with the proximal point method is well-understood, the convergence rate for BALM has not yet been thoroughly studied in the literature. We analyze, in this thesis, the convergence rates of BALM in terms of the …
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Data Mining with Newton's Method.
… to data mining of technical data. Several strategies are employed to stabilize Newton's method to pathological function behavior. NM is compared to GAs and to the simplex evolutionary operation algorithm (EVOP). We find that GAs, NM, and EVOP all perform efficiently for well-behaved global …
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Mathematical analysis of a dynamical system for sparse recovery
… of this thesis are threefold. First, convergence results for neural networks that solve a large class of nonsmooth optimization programs are presented. These results extend previous analysis by allowing the interconnection matrix to be singular and the activation function to have many …
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A functional link neural network with modified cuckoo search for prediction tasks
… has still been facing problems which the convergence rate is very low due to the multi layering topology of the network. Thus, this research proposed an implementation of Functional Link Neural Network (FLNN) which composed of a single layer of tunable weight trained with the Modified …
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GPU-accelerated Linear Solvers for High-order Finite Element Methods in Poisson Problems
… methods and algorithms aimed at improving the convergence and efficiency of the preconditioned conjugate gradient (PCG) algorithm for high-order finite element methods on Graphics Processing Units (GPUs). The conjugate gradient algorithm iteratively refines an initial approximate solution until …
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Stability of machine learning algorithms
… variability of linear decision boundaries generated from homogenous training samples. Incorporating DBI with the generalization error (GE), we propose a two-stage algorithm for selecting the <em>most accurate and stable</em> classifier. The proposed classifier selection method introduces the …
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Implementation and evaluation of echo cancellation algorithms
… system. The impedance mismatch in hybrids generates network (electric) echo. The acoustic coupling between loudspeaker and microphone, in hands-free telephones, produces acoustic echo. Echo cancelers are used to control these echoes. In this thesis, we analyze the Least Mean Squares (LMS), …
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Error estimates for finite difference solutions of second-order elliptic equations in discrete Sobolev spaces
… Based on these lp-estimates, we obtain the convergence rate of the approximate solutions and their difference quotients in the sup norm.
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Iterative Finite-Difference Solution of Heat Transfer and Fluid Flow With Truncated Modal Acceleration and Imaginary Time (Algorithm, Modeling, Steady-State)
This work discusses acceleration of the convergence of some classic point-iterative methods; Jacobi, simultaneous overrelaxation (JOR), Gauss-Seidel and successive overrelaxation (SOR). Each of these methods is diffusive in nature. Such methods do not distribute calculated changes of mass, …
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Multigrid Algorithms for Massively Parallel Machines
… The additional computation improves the convergence rate of the multigrid algorithm and thus reduces the total parallel execution time to solve a problem. The second algorithm, the <em>Chopped Parallel Multigrid</em> (<em>CPMG</em>) algorithm, reduces the computational work on the coarse …
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Hamiltonian Paths and Strands for Unified Grid Approach for Computing Aerodynamic Flows
… structured grid. The numerical accuracy and convergence rate are investigated under various flow conditions. The numerical efficiency was improved with a line-implicit method compared to a point-implicit method on the unstructured grid. Both stencil- and gradient-based reconstructions are …
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Some new results for solving linear systems arising from computational fluid dynamics problems
… methods to handle them. We study how the convergence rate of the outer iteration is related to the convergence rate of the inner iterations. For symmetric positive definite systems, we propose a class of nested preconditioners and analyze properties of these preconditioners. Some necessary …
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Analysis and Development of Blind Adaptive Beamforming Algorithms
… here, including analytic results on the convergence rate. Previous results have relied on Monte Carlo simulation. This framework is also used to propose a new class of blind adaptive algorithms that offer the potential for improved convergence rate.
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