The aim is to develop vibration control of flexible spacecraft by adaptive controller. A case study will be carried out which simulates planar motion of flexible spacecraft as a coupled hybrid dynamics of rigid body motion and the flexible arm vibration. The notch filter and adaptive vibration controller, which updates filter and controller parameters continuously from the sensor measurement, a...

In this paper we obtain upper and lower bounds for the H 1 norm of the Kalman lter and RLS algorithm, with respect to prediction and ltered errors. These bounds can be used to study the robustness properties of such estimators. One main conclusion is that, unlike H 1-optimal estimators which do not allow for any ampliication of the disturbances, the least-squares estimators do allow for such am...

We develop an efficient adaptive receiver for joint equalization and interfercnce cancellation for multi-user space-time blockbcoded transmissions. The receiver exploits the rich code suucture and allows multiple user transmissions over frequency-selective fading channels with reduced compleiity and lower system overhead. The adaptation scheme is based on a recursive least-squares implementatio...

The Adaptive Least Squares Correlation is a very potent and flexible technique for all kinds of data matching problems. Here its application to image matching is outlined. It allows for simultaneous radiometric corrections and local geometrical image shaping, whereby the system parameters are automatically assessed, corrected, and thus optimized during the least squares iterations. The various ...

Historic parchment is an extremely complex material, not only due to the various methods of production used and various past environmental histories of objects, but also due to its inhomogeneous structure. Many traditional methods of characterisation are empirical, but useful since they have gained recognition by the end-users. In this paper, we investigated the shrinkage temperature of collage...

A new non-linear Recursive Least Squares (RLS) algorithm is presented in the context of pattern classification problems. The algorithm incorporates the non-linearity of the filter’s output in the updating rules of the classical RLS algorithm. The proposed method yields lower stationary error levels when compared to the standard LMS and RLS algorithms in a classical application of pattern classi...

We derive optimal estimators of a linear combination of the responses, under the random permutation model, incorporating auxiliary information and response error. In particular, we propose estimators of a measure of association, that is named B and defined farther in (1), between a response and an explanatory variable based on a simple random sample obtained without replacement from a finite po...

Consider the problem of estimating a function f known to lie in a convex, compact subset F of L2[0, 1], when one observes data on f containing white Gaussian noise. We establish an upper bound on the integrated mean-squared error of least-squares estimates which uses the asymptotic properties of the Gel'fand n-widths of F. The bound shows that if the Gel'fand n-widths tend to zero at a faster r...