Final Report Buffalo National River Ecosystems Part IV

Sampling point locations and analytical procedures remained unchanged from those outlined in previous Buffalo National River Ecosystem reports. The only significant change in analytical procedures was a reversion to the glass fiber filter method for collection and extraction of samples for chlorophyll analysis. This change was neeessitated by a need for filtering a larger volume to obtain enough chlorophyll for an accurate measurement. Samples were collected monthly from April 9 through December 30. No samples were taken in January or February due to the extremely uncertain traveling conditions caused by the frequent snows. Prior research indicates that the December 30 sample is sufficiently reflective of stable winter conditions to obviate the need for more winter samples (see previous reports)

Shape control of large space structures

A survey has been conducted to determine the types of control strategies which have been proposed for controlling the vibrations in large space structures. From this survey several representative control strategies were singled out for detailed analyses. The application of these strategies to a simplified model of a large space structure has been simulated. These simulations demonstrate the implementation of the control algorithms and provide a basis for a preliminary comparison of their suitability for large space structure control

Momentum-Space Approach to Asymptotic Expansion for Stochastic Filtering

This paper develops an asymptotic expansion technique in momentum space for stochastic filtering. It is shown that Fourier transformation combined with a polynomial-function approximation of the nonlinear terms gives a closed recursive system of ordinary differential equations (ODEs) for the relevant conditional distribution. Thanks to the simplicity of the ODE system, higher order calculation can be performed easily. Furthermore, solving ODEs sequentially with small sub-periods with updated initial conditions makes it possible to implement a substepping method for asymptotic expansion in a numerically efficient way. This is found to improve the performance significantly where otherwise the approximation fails badly. The method is expected to provide a useful tool for more realistic financial modeling with unobserved parameters, and also for problems involving nonlinear measure-valued processes.Comment: revised version for publication in Ann Inst Stat Mat