Browsing Mathematics (Faculty of) by Subject "symbolic computation"
Now showing items 1-6 of 6
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Computational Methods for Combinatorial and Number Theoretic Problems
(University of Waterloo, 2017-04-27)Computational methods have become a valuable tool for studying mathematical problems and for constructing large combinatorial objects. In fact, it is often not possible to find large combinatorial objects using human ... -
Computing a Basis for an Integer Lattice
(University of Waterloo, 2022-12-22)The extended gcd problem takes as input two integers, and asks as output an integer linear combination of the integers that are equal to their gcd. The classical extended Euclidean algorithm and fast variants such as the ... -
Efficient Computation with Sparse and Dense Polynomials
(University of Waterloo, 2011-04-26)Computations with polynomials are at the heart of any computer algebra system and also have many applications in engineering, coding theory, and cryptography. Generally speaking, the low-level polynomial computations of ... -
Homotopy algorithms for solving structured determinantal systems
(University of Waterloo, 2020-12-17)Multivariate polynomial systems arising in numerous applications have special structures. In particular, determinantal structures and invariant systems appear in a wide range of applications such as in polynomial optimization ... -
MathBrush web application: Design and implementation of an online pen-input interface for computer algebra systems
(University of Waterloo, 2017-08-15)Several pen-math systems have been developed for mobile and tablet platforms, most notably by the MathBrush project. With the increasing variety of available devices and platforms used by students, this thesis aims to ... -
Sparse Polynomial Interpolation and Testing
(University of Waterloo, 2016-03-03)Interpolation is the process of learning an unknown polynomial f from some set of its evaluations. We consider the interpolation of a sparse polynomial, i.e., where f is comprised of a small, bounded number of terms. Sparse ...