Now showing items 11-16 of 16
Efficient and Accurate Simulation of Integrate-and-Fire Neuronal Networks in the Hippocampus
This thesis evaluates a method of computing highly accurate solutions for network simulations of integrate-and-fire (IAF) neurons. Simulations are typically evolved using time-stepping, but since the IAF model is composed ...
Parallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm
This paper describes a Parallel Space Decomposition (PSD) technique for the Mesh Adaptive Direct Search (MADS) algorithm. MADS extends Generalized Pattern Search for constrained nonsmooth optimization problems. The objective ...
A MADS Algorithm with a Progressive Barrier for Derivative-Free Nonlinear Programming
We propose a new algorithm for general constrained derivative-free optimization. As in most methods, constraint violations are aggregated into a single constraint violation function. As in filter methods, a threshold, or ...
Best Symmetric Low Rank Approximation Via the Symmetry Preserving Singular Value Decomposition
The symmetry preserving singular value decomposition (SPSVD) produces the best symmetric (low rank) approximation to a set of data. These symmetric approximations are characterized via an invariance under the action of a ...
Domain Decomposition and Model Reduction of Systems with Local Nonlinearities
The goal of this paper is to combine balanced truncation model reduction and domain decomposition to derive reduced order models with guaranteed error bounds for systems of discretized partial differential equations (PDEs) ...
A Comparison of Three Total Variation Based Texture Extraction Models
This paper qualitatively compares three recently proposed models for signal/image texture extraction based on total variation minimization:the Meyer, Vese-Osher, and TV-L1 models. We formulate discrete versions of these ...