16 research outputs found
Balayage of Fourier Transforms and the Theory of Frames
Every separable Hilbert space has an orthogonal basis. This allows every element in the Hilbert space to be expressed as an infinite linear combination of the basis elements. The structure of a basis can be too rigid in some situations. Frames gives us greater flexibility than bases. A frame in Hilbert space is a spanning set with the reconstruction property.
A frame must satisfy both an upper frame bound and a lower frame bound. The requirement of an upper bound is rather modest. Most of the mathematical difficulty lies in showing the lower bound exists.
We examine the theory of Beurling on Balayage of Fourier transforms and the role of spectral synthesis in this theory. Beurling showed that if the condition of Balayage holds, then the lower frame bound for a Fourier frame exists under suitable hypothesis. We extend this theory to obtain lower bound inequalities for other types of frames. We prove that lower bounds exist for generalized Fourier frames and two types of semi-discrete Gabor frames
Exact Recovery of Prototypical Atoms through Dictionary Initialization
In dictionary learning, a matrix comprised of signals Y is factorized into the product of two matrices: a matrix of prototypical atoms D, and a sparse matrix containing coefficients for atoms in D, called X. Dictionary learning finds applications in signal processing, image recognition, and a number of other fields. Many algorithms for solving the dictionary learning problem follow the alternating minimization paradigm; that is, by alternating solving for D and X. In 2014, Agarwal et al. proposed a dictionary initialization procedure that is used before this alternating minimization process. We show that there is a modification to this initialization algorithm and a corresponding data generating process under which full recovery of D is possible without a subsequent alternating minimization procedure. Our findings indicate that the costly step of alternating minimization can be bypassed, and that other data models may enjoy the same features as the one we propose
Random Walks in the Quarter Plane: Solvable Models with an Analytical Approach
Initially, an urn contains 3 blue balls and 1 red ball. A ball is randomly chosen from the urn. The ball is returned to the urn, together with one additional ball of the same type (red or blue). When the urn has twenty balls in it, what is the probability that exactly ten balls are blue? This is a model for a random process. This urn model has been extended in various ways and we consider some of these generalizations. Urn models can be formulated as random walks in the quarter plane. Our findings indicate that for a specific type of random walk, we can calculate the generating function explicitly. Instead of using Markov chains, our approach is to use analytical techniques from differential equations
Triangulation and finite element method for a variational problem inspired by medical imaging
We implement the finite element method to solve a variational problem that is inspired by medical imaging. In our application, the domain of the image does not need to be a rectangle and can contain a cavity in the middle. The standard approach to solve a variational problem involves formulating the problem as a partial differential equation. Instead, we solve the variational problem directly, using only techniques available to anyone familiar with vector calculus. As part of the computation, we also explore how triangulation is a useful tool in the process
Signal Processing on Graphs Using Kron Reduction and Spline Interpolation
In applications such as image processing, the data is given in a regular pattern with a known structure, such as a grid of pixels. However, it is becoming increasingly common for large datasets to have some irregular structure. In image recognition, one of the most successful methods is wavelet analysis, also commonly known as multi-resolution analysis. Our project is to develop and explore this powerful technique in the setting where the data is not stored in the form of a rectangular table with rows and columns of pixels. While the data sets will still have a lot of structure to be exploited, we want to extend the wavelet analysis to the setting when the data structure resembles is more like a network than a rectangular table. Networks provide a flexible generalization of the rigid structure of rectangular tables