Now showing items 201-209 of 209
Numerical Solutions of Matrix Equations Arising in Model Reduction of Large-Scale Linear-Time-Invariant Systems
This thesis presents and analyzes new algorithms for matrix equations arising from model reduction of linear-time-invariant (LTI) systems. Such systems arise in a variety of areas, especially in circuit simulation. When ...
Dimension Reduction for Unsteady Nonlinear Partial Differential Equations via Empirical Interpolation Methods
This thesis evaluates and compares the efficiencies of techniques for constructing reduced-order models for finite difference (FD) and finite element (FE) discretized systems of unsteady nonlinear partial differential ...
A C++ Class Supporting Adjoint-State Methods
The adjoint-state method is widely used for computing gradients in simulation- driven optimization problems. The adjoint-state evolution equation requires access to the entire history of the system states. There are ...
Alternating Direction Algorithms for L1-Problems in Compressive Sensing
In this paper, we propose and study the use of alternating direction algorithms for several L1-norm minimization problems arising from sparse solution recovery in compressive sensing, including the basis pursuit problem, ...
Analysis of Weak Solutions For the Fully Coupled Stokes-Darcy-Transport Problem
This paper analyzes the surface/subsurface flow coupled with transport. The flow is modeled by the coupling of Stokes and Darcy equations. The transport is modeled by a convection-dominated parabolic equation. The two-way ...
Image-Based Face Illumination Transferring Using Logarithmic Total Variation Models
In this paper, we present a novel image-based technique that transfers illumination from a source face image to a target face image based on the Logarithmic Total Variation (LTV) model. Our method does not require any prior ...
Time-Stepping Classes for Optimization (TSOpt)
This report introduces the "Time Stepping Package for Optimization", or TSOpt, which is an interface for time-stepping simulation written in C++. It packages a simulator together with its derivatives (\sensitivities") and ...
Collaborative Spectrum Sensing from Sparse Observations Using Matrix Completion
In cognitive radio, spectrum sensing is a key component to detect spectrum holes (i.e., channels not used by any primary users). Collaborative spectrum sensing among the cognitive radio nodes is expected to improve the ...
A Matlab Implementation of a Flat Norm Motivated Polygonal Edge Matching Method using a Decomposition of Boundary into Four 1-Dimensional Currents
We describe and provide code and examples for a polygonal edge matching method.