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Two common classes of filter functions in use today, Butterworth functions and Chebyshev functions, are based upon solutions to special cases of the Sturm-Liouville equation. Here, solutions to several other special cases of the Sturm-Liouville equation were used to develop filter functions, and the properties of the resulting filters were examined. The following functions were explored: Chebyshev functions of the second kind, untraspherical functions of the second and third kinds, Hermite functions, and Legendre functions. Filter functions were developed for each of the first five polynomials in each series of functions, and magnitude and phase responses were tabulated and plotted. One of the classes of functions, the Hermite functions, led to filters which have a significant advantage over the commonly used Chebyshev filters in passband magnitude response, and were essentially the same as Chebyshev filters in stopband magnitude response and phase response.

<p>We are interested in backward-in-time solution techniques for evolutionary PDE problems arising in fluid mechanics. In addition to their intrinsic interest, such techniques have applications in recently proposed retrograde data assimilation. As our model system we consider the terminal value problem for the Kuramoto-Sivashinsky equation in a l D periodic domain. The Kuramoto-Sivashinsky equation, proposed as a model for interfacial and combustion phenomena, is often also adopted as a toy model for hydrodynamic turbulence because of its multiscale and chaotic dynamics. Such backward problems are typical examples of ill-posed problems, where any disturbances are amplified exponentially during the backward march. Hence, regularization is required to solve such problems efficiently in practice. We consider regularization approaches in which the original ill-posed problem is approximated with a less ill-posed problem, which is achieved by adding a regularization term to the original equation. While such techniques are relatively well-understood for linear problems, it is still unclear what effect these techniques may have in the nonlinear setting. In addition to considering regularization terms with fixed magnitudes, we also explore a novel approach in which these magnitudes are adapted dynamically using simple concepts from the Control Theory.</p> / Thesis / Master of Science (MSc)