M. Coderch ... [et al.]. / Bibliography: leaf 6. / "September, 1981." / Supported in part by the DOE under Grant ET-76-C-01-2295

Splines are piecewise polynomial functions of a given order of smoothness r on a triangulated region (or polyhedrally subdivided region) of Rd. The set of splines of degree at most k forms a vector space Crk() Moreover, a nice way to study Cr k()is to embed n Rd+1, and form the cone b of with the origin. It turns out that the set of splines on b is a graded module Cr b() over the polynomial ring R[x1; : : : ; xd+1], and the dimension of Cr k() is the dimension o This dissertation follows the works of Billera and Rose, as well as Schenck and Stillman, who each approached the study of splines from the viewpoint of homological and commutative algebra. They both defined chain complexes of modules such that Cr(b) appeared as the top homology module. First, we analyze the effects of gluing planar simplicial complexes. Suppose 1, 2, and = 1 [ 2 are all planar simplicial complexes which triangulate pseudomanifolds. When 1 \ 2 is also a planar simplicial complex, we use the Mayer-Vietoris sequence to obtain a natural relationship between the spline modules Cr(b), Cr (c1), Cr(c2), and Cr( \ 1 \ 2). Next, given a simplicial complex , we study splines which also vanish on the boundary of. The set of all such splines is denoted by Cr(b). In this case, we will discover a formula relating the Hilbert polynomials of Cr(cb) and Cr (b). Finally, we consider splines which are defined on a polygonally subdivided region of the plane. By adding only edges to to form a simplicial subdivision , we will be able to find bounds for the dimensions of the vector spaces Cr k() for k 0. In particular, these bounds will be given in terms of the dimensions of the vector spaces Cr k() and geometrical data of both and . This dissertation concludes with some thoughts on future research questions and an appendix describing the Macaulay2 package SplineCode, which allows the study of the Hilbert polynomials of the spline modules.

In electrical engineering, the designer is often presented with the problem of synthesizing a circuit for which the mathematical specifications are unsuitable for physical realization. Hence, the engineer must approximate as well as possible the prescribed network function by another function which is realizable. This paper describes a new approximation method for solving the problem of realizing passive network transfer functions, where the realization is carried out through the use of passive, reciprocal,lumped, linear, and time-invariant elements.

Approximation and interpolation employing radial basis functions has found important applications since the early 1980's in areas such as signal processing, medical imaging, as well as neural networks. Several applications demand that certain physical properties be fulfilled, such as a function being divergence free. No such class of radial basis functions that reflects these physical properties was known until 1994, when Narcowich and Ward introduced a family of matrix-valued radial basis functions that are divergence free. They also obtained error bounds and stability estimates for interpolation by means of these functions. These divergence-free functions are very smooth, and have unbounded support. In this thesis we introduce a new class of matrix-valued radial basis functions that are divergence free as well as compactly supported. This leads to the possibility of applying fast solvers for inverting interpolation matrices, as these matrices are not only symmetric and positive definite, but also sparse because of this compact support. We develop error bounds and stability estimates which hold for a broad class of functions. We conclude with applications to the numerical solution of the Navier-Stokes equation for certain incompressible fluid flows.

To solve the linear equation Ax = f, where f is an element of Hilbert space H and A is a positive definite operator such that the spectrum (T (A) ( [m,M] , we approximate -1 the inverse operator A by an operator V which is a polynomial in A. Using the spectral theory of bounded normal operators the problem is reduced to that of approximating a function of the real variable by polynomials of best uniform approximation. We apply two different techniques of evaluating A-1 so that the operator V is chosen either as a polynomial P (A) when P (A) approximates the n n function 1/A on the interval [m,M] or a polynomial Qn (A) when 1 - A Qn (A) approximates the function zero on [m,M]. The polynomials Pn (A) and Qn (A) satisfy three point recurrence relations, thus the approximate solution vectors P (A)f n and Q (A)f can be evaluated iteratively. We compare the procedures involving n Pn (A)f and Qn (A)f by solving matrix vector systems where A is positive definite. We also show that the technique can be applied to an operator which is not selfadjoint, but close, in the sense of operator norm, to a selfadjoint operator. The iterative techniques we develop are used to solve linear systems arising from the discretization of Freedholm integral equations of the second kind. Both smooth and weakly singular kernels are considered. We show that earlier work done on the approximation of linear functionals < x,g > , where 9 EH, involve a zero order approximation to the inverse operator and are thus special cases of a general result involving an approximation of arbitrary degree to A -1 . / Thesis (Ph.D.)-University of Natal, 1994.

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Most combinatorial optimization problems are NP -hard, which imply that under well- believed complexity assumptions, there exist no polynomial time algorithms to solve them. To cope with the NP-hardness, approximation algorithms which return solutions close to the optimal, have become a rich field of study. One successful method for designing approx- imation algorithms has been to model the optimization problem as an integer program and then using its polynomial time solvable linear programming relaxation for the design and analysis of such algorithms. Such a technique is called the LP-based technique. In this thesis, we study the algorithmic aspects of three classes of combinatorial optimization problems using LP-based techniques as our main tool. Connectivity Problems: We study the Steiner tree problem and devise new linear pro- gramming relaxations for the problem. We show an equivalence of our relaxation with the well studied bidirected cut relaxation for the Steiner tree problem. Furthermore, for a class of graphs called quasi-bipartite graphs, we improve the best known upper bound on the integrality gap from 3/2 to 4/3. Algorithmically, we obtain fast and simple approximation algorithms for the Steiner tree problem on quasi-bipartite graphs. Allocation Problems: We study the budgeted al location problem of allocating a set of indivisible items to a set of agents who bid on it but possess a hard budget constraint more than which they are unwilling to pay. This problem is a special case of submodular welfare maximization. We use a natural LP relaxation for the problem and improve the best known approximation factor for the problem from ~ 0.632 to 3/4. We also improve the inapprox- imability factor of the problem to 15/16 and use our techniques to show inapproximability results for many other allocation problems. We also study online allocation problems where the set of items are unknown and appear one at a time. Under some necessary assumptions we provide online algorithms for many problems which attain the (almost) optimal competitive ratio. Both these works have applications in the area of budgeted auctions, the most famous of which are the sponsored search auctions hosted by search engines on the Internet. Design Problems: We formally define and study design problems which asks how the weights of an input instance can be designed, so that the minimum (or maximum) of a certain function of the input can be maximized (respectively, minimized). We show if the function can be approximated to any factor $alpha$, then the optimum design can be approximated to the same factor. We also show that (max-min) design problems are dual to packing problems. We use the framework developed by our study of design problems to obtain results about fraction- ally packing Steiner trees in a "black-box" fashion. Finally, we study integral packing of spanning trees and provide an alternate proof of a theorem of Nash-Williams and Tutte about packing spanning trees.

Thesis (M. S.)--Aerospace Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Mavris, Dimitri; Committee Member: Biltgen, Patrick; Committee Member: Ender, Tommer.

Thesis (Ph. D.)--Aerospace Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Olivier A. Bauchau; Committee Member: Andrew Makeev; Committee Member: Carlo L. Bottasso; Committee Member: Dewey H. Hodges; Committee Member: Massimo Ruzzene. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2007. / Lu, Jye-Chyi, Committee Member ; Shaprio, Alexander, Committee Member ; Amemiya, Yasuo, Committee Co-Chair ; Wu, C. F. Jeff, Committee Chair ; Vengazhiyil, Roshan Joseph, Committee Member.