On Lyapunov stability analyses of the switching regulator/filtersystem

The stability design criteria for the fourth-order switching regulator/low-pass filter system are obtained directly from the solution to the resultant simultaneous equations for the Lyapunov matrix equation. The regulator/filter system is asymptotically stable if the values of the filter components are chosen to satisfy the derived Lyapunov stability design criterion for a given value of the switcher dynamic resistance     

Cosmic-ray antiprotons in the galaxy

A key issue in fundamental physics is the nature of non-baryonic dark matter in the universe. Among the candidates proposed by the particle physics community are neutralinos whose annihilation in the Galactic halo can produce antiprotons with a characteristic spectrum. Several balloon and space borne experiments have been actively looking to detect the neutralino signature in cosmic antiprotons. This task is however hampered by the existence of a secondary “background” flux of antiprotons produced in the interactions of cosmic-ray particles in the interstellar medium. A notable difficulty is that a self-consistent and complete model of cosmic-ray propagation in the Galaxy has thus far been elusive. When subtracting the secondary background from the observed data, it is therefore critical that all viable models of secondary cosmic-ray antiproton propagation be thoroughly examined, and all uncertainties stemming from plurality of the models be duly considered. In this paper we concentrate on three particular models of Diffusion, Galactic Wind, and Distributed Stochastic Reacceleration, and discuss the predicted antiproton spectrum in each model.     

Properties and performance of extended target motion analysis

The problem of target motion analysis (TMA) has been the subject of an important literature. However, present methods use data estimated by a short time analysis (azimuths, Dopplers, etc.). For far sources, the nonstationarities of the array processing outputs, induced by the sources motion, may be simply modeled. This model leads one to consider directly a spatio-temporal TMA. Then new (spatio-temporal) data can be estimated. These estimates correspond to a long time analysis. Further, note that they are estimated independently of the (classical) bearings. In this general framework, the concept of source trajectory replaces the classical instantaneous bearings. Corresponding TMA algorithms are then studied. Then the study of statistical performance is carefully studied     

Sequence comparison techniques for multisensor data fusion andtarget recognition

A new class of techniques for multisensor fusion and target recognition is proposed using sequence comparison by dynamic programming and multiple model estimation. The objective is to fuse information on the kinematic state and “nonkinematic” signature of unclassified targets, assessing the joint likelihood of all observed events for recognition. Relationships are shown to previous efforts in pattern recognition and state estimation. This research applies “classical” speech processing-related and other sequence comparison methods to moving target recognition, extends the efforts of previous researchers through improved fusion with kinematic information, relates the proposed techniques to Bayesian theory, and applies parameter identification methods to target recognition for improved understanding of the subject in general. The proposed techniques are evaluated and compared with existing approaches using the method of generalized ambiguity functions, which lends to a form of Cramer-Rao lower bound for target recognition     

Influence of long-term altered gravity on the swimming performance of developing cichlid fish: including results from the 2nd German Spacelab Mission D-2.

This study presents qualitative and quantitative data concerning gravity-dependent changes in the swimming behaviour of developing cichlid fish larvae (Oreochromis mossambicus) after a 9 resp. 10 days exposure to increased acceleration (centrifuge experiments), to reduced gravity (fast-rotating clinostat), changed accelerations (parabolic aircraft flights) and to near weightlessness (2nd German Spacelab Mission D-2). Changes of gravity initially cause disturbances of the swimming performance of the fish larvae. With prolonged stay in orbit a step by step normalisation of the swimming behaviour took place in the fish. After return to 1g earth conditions no somersaulting or looping could be detected concerning the fish, but still slow and disorientated movements as compared to controls occurred. The fish larvae adapted to earth gravity within 3-5 days. Fish seem to be in a distinct early developmental stages extreme sensitive and adaptable to altered gravity; However, elder fish either do not react or show compensatory behaviour e.g. escape reactions.     

Enzyme conversion of lignocellulosic plant materials for resource recovery in a Controlled Ecological Life Support System.

A large amount of inedible plant material composed primarily of the carbohydrate materials cellulose, hemicellulose, and lignin is generated as a result of plant growth in a Controlled Ecological Life-Support System (CELSS). Cellulose is a linear homopolymer of glucose, which when properly processed will yield glucose, a valuable sugar because it can be added directly to human diets. Hemicellulose is a heteropolymer of hexoses and pentoses that can be treated to give a sugar mixture that is potentially a valuable fermentable carbon source. Such fermentations yield desirable supplements to the edible products from hydroponically-grown plants such as rapeseed, soybean, cowpea, or rice. Lignin is a three-dimensionally branched aromatic polymer, composed of phenyl propane units, which is susceptible to bioconversion through the growth of the white rot fungus, Pluerotus ostreatus. Processing conditions, that include both a hot water pretreatment and fungal growth and that lead to the facile conversion of plant polysaccharides to glucose, are presented.     

AFIT neural network research

A brief summary of research done at the Air Force Institute of Technology (AFIT) in the area of neural networks is provided. It has been shown that backpropagation, used for feedforward artificial neural networks, is just a degenerate version of an extended Kalman filter, and that networks can do about as well as the optimum statistical classification technique. A method of finding the importance of features for use by a neural network classifier has been determined. Techniques for using neural networks for image segmentation have been developed. In optical pattern recognition, techniques that allow the processing of real FLIR (forward-looking infrared) images with existing binary spatial light modulators have been devised. An optical direction of arrival detector applicable to laser illumination direction determination has been designed and tested; the design is similar to a fly's eye. Coated mirrors for the optical confocal Fabry-Perot interferometer have been designed, specified, fabricated, and installed. Significant progress has been made in the use of neural networks for processing multiple-feature sets for speech recognition     

Practical stabilization in attitude thruster control

The attitude stabilization of a spacecraft using thrusters is considered from a practical point of view, i.e., when actuator constraints, uncertainties and failures, measurement noise, fuel consumption, and inertia matrix uncertainty are considered. A variable structure controller based on sliding modes is obtained first, which guarantees global exponential stability under actuator constraints, uncertainties, and failures. The design is based on a continuous average-proportional torque selection function and a set of feasible sliding surfaces, which may be adapted to improve performance. Exponential convergence towards ultimate bounds is guaranteed when all other practical issues arise.     

A wavelet multiresolution analysis for spatio-temporal signals

The wavelet filters of the conventional 3D multiresolution analysis possess homogeneous spatial and temporal frequency characteristics which limits one's ability to match filter frequency characteristics to signal frequency behavior. Also, the conventional 3D multiresolution analysis employs an oct-tree decomposition structure which restricts the analysis of signal details to identical resolutions in space and time. This paper presents a 3D wavelet multiresolution analysis constructed from nonhomogeneous spatial and temporal filters, and an orthogonal sub-band coding scheme that decouples the spatial and temporal decomposition processes