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At least 1,099 records · Page 61

Crossbar Switches For Optical Data-Communication Networks

Optoelectronic and electro-optical crossbar switches called "permutation engines" (PE's) developed to route packets of data through fiber-optic communication networks. Basic network concept described in "High-Speed Optical Wide-Area Data-Communication Network" (NPO-18983). Nonblocking operation achieved by decentralized switching and control scheme. Each packet routed up or down in each column of this 5-input/5-output permutation engine. Routing algorithm ensures each packet arrives at its designated output port without blocking any other packet that does not contend for same output port.

Monacos, Steve P.↗

Laser ranging network performance and routine orbit determination at D-PAF

ERS-1 is now about 8 months in orbit and has been tracked by the global laser network from the very beginning of the mission. The German processing and archiving facility for ERS-1 (D-PAF) is coordinating and supporting the network and performing the different routine orbit determination tasks. This paper presents details about the global network status, the communication to D-PAF and the tracking data and orbit processing system at D-PAF. The quality of the preliminary and precise orbits are shown and some problem areas are identified.

Massmann, Franz-Heinrich↗

Bandwidth characteristics of multimedia data traffic on a local area network

Limited spacecraft communication links call for users to investigate the potential use of video compression and multimedia technologies to optimize bandwidth allocations. The objective was to determine the transmission characteristics of multimedia data - motion video, text or bitmap graphics, and files transmitted independently and simultaneously over an ethernet local area network. Commercial desktop video teleconferencing hardware and software and Intel's proprietary Digital Video Interactive (DVI) video compression algorithm were used, and typical task scenarios were selected. The transmission time, packet size, number of packets, and network utilization of the data were recorded. Each data type - compressed motion video, text and/or bitmapped graphics, and a compressed image file - was first transmitted independently and its characteristics recorded. The results showed that an average bandwidth of 7.4 kilobits per second (kbps) was used to transmit graphics; an average bandwidth of 86.8 kbps was used to transmit an 18.9-kilobyte (kB) image file; a bandwidth of 728.9 kbps was used to transmit compressed motion video at 15 frames per second (fps); and a bandwidth of 75.9 kbps was used to transmit compressed motion video at 1.5 fps. Average packet sizes were 933 bytes for graphics, 498.5 bytes for the image file, 345.8 bytes for motion video at 15 fps, and 341.9 bytes for motion video at 1.5 fps. Simultaneous transmission of multimedia data types was also characterized. The multimedia packets used transmission bandwidths of 341.4 kbps and 105.8kbps. Bandwidth utilization varied according to the frame rate (frames per second) setting for the transmission of motion video. Packet size did not vary significantly between the data types. When these characteristics are applied to Space Station Freedom (SSF), the packet sizes fall within the maximum specified by the Consultative Committee for Space Data Systems (CCSDS). The uplink of imagery to SSF may be performed at minimal frame rates and/or within seconds of delay, depending on the user's allocated bandwidth. Further research to identify the acceptable delay interval and its impact on human performance is required. Additional studies in network performance using various video compression algorithms and integrated multimedia techniques are needed to determine the optimal design approach for utilizing SSF's data communications system.

Chuang, Shery L.↗

Training product unit neural networks with genetic algorithms

The training of product neural networks using genetic algorithms is discussed. Two unusual neural network techniques are combined; product units are employed instead of the traditional summing units and genetic algorithms train the network rather than backpropagation. As an example, a neural netork is trained to calculate the optimum width of transistors in a CMOS switch. It is shown how local minima affect the performance of a genetic algorithm, and one method of overcoming this is presented.

Janson, D. J.↗

VLSI synthesis of digital application specific neural networks

Neural networks tend to fall into two general categories: (1) software simulations, or (2) custom hardware that must be trained. The scope of this project is the merger of these two classifications into a system whereby a software model of a network is trained to perform a specific task and the results used to synthesize a standard cell realization of the network using automated tools.

Beagles, Grant↗

The automated ground network system

The primary goal of the Automated Ground Network System (AGNS) project is to reduce Ground Network (GN) station life-cycle costs. To accomplish this goal, the AGNS project will employ an object-oriented approach to develop a new infrastructure that will permit continuous application of new technologies and methodologies to the Ground Network's class of problems. The AGNS project is a Total Quality (TQ) project. Through use of an open collaborative development environment, developers and users will have equal input into the end-to-end design and development process. This will permit direct user input and feedback and will enable rapid prototyping for requirements clarification. This paper describes the AGNS objectives, operations concept, and proposed design.

Smith, Miles T.↗

Study on networking issues of medium earth orbit satellite communications systems

Two networking issues of communications systems with medium earth orbit (MEO) satellites, namely network architectures and location determination and registration methods for hand-held terminals, are investigated in this paper. For network architecture, five candidate architectures are considered and evaluated in terms of signaling traffic. For location determination and registration, two methods are discussed and evaluated.

Araki, Noriyuki↗

The design and networking of dynamic satellite constellations for global mobile communication systems

Various design factors for mobile satellite systems, whose aim is to provide worldwide voice and data communications to users with hand-held terminals, are examined. Two network segments are identified - the ground segment (GS) and the space segment (SS) - and are seen to be highly dependent on each other. The overall architecture must therefore be adapted to both of these segments, rather than each being optimized according to its own criteria. Terrestrial networks are grouped and called the terrestrial segment (TS). In the SS, of fundamental importance is the constellation altitude. The effect of the altitude on decisions such as constellation design choice and on network aspects like call handover statistics are fundamental. Orbit resonance is introduced and referred to throughout. It is specifically examined for its useful properties relating to GS/SS connectivities.

Cullen, Cionaith J.↗

Adaptive nonlinear polynomial neural networks for control of boundary layer/structural interaction

The acoustic pressures developed in a boundary layer can interact with an aircraft panel to induce significant vibration in the panel. Such vibration is undesirable due to the aerodynamic drag and structure-borne cabin noises that result. The overall objective of this work is to develop effective and practical feedback control strategies for actively reducing this flow-induced structural vibration. This report describes the results of initial evaluations using polynomial, neural network-based, feedback control to reduce flow induced vibration in aircraft panels due to turbulent boundary layer/structural interaction. Computer simulations are used to develop and analyze feedback control strategies to reduce vibration in a beam as a first step. The key differences between this work and that going on elsewhere are as follows: that turbulent and transitional boundary layers represent broadband excitation and thus present a more complex stochastic control scenario than that of narrow band (e.g., laminar boundary layer) excitation; and secondly, that the proposed controller structures are adaptive nonlinear infinite impulse response (IIR) polynomial neural network, as opposed to the traditional adaptive linear finite impulse response (FIR) filters used in most studies to date. The controllers implemented in this study achieved vibration attenuation of 27 to 60 dB depending on the type of boundary layer established by laminar, turbulent, and intermittent laminar-to-turbulent transitional flows. Application of multi-input, multi-output, adaptive, nonlinear feedback control of vibration in aircraft panels based on polynomial neural networks appears to be feasible today. Plans are outlined for Phase 2 of this study, which will include extending the theoretical investigation conducted in Phase 2 and verifying the results in a series of laboratory experiments involving both bum and plate models.

Parker, B. Eugene, Jr.↗

Optimal Space Station solar array gimbal angle determination via radial basis function neural networks

The potential for excessive plume impingement loads on Space Station Freedom solar arrays, caused by jet firings from an approaching Space Shuttle, is addressed. An artificial neural network is designed to determine commanded solar array beta gimbal angle for minimum plume loads. The commanded angle would be determined dynamically. The network design proposed involves radial basis functions as activation functions. Design, development, and simulation of this network design are discussed.

Clancy, Daniel J.↗

A neural network with modular hierarchical learning

This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

Baldi, Pierre F.↗

MARSNET: A European network of stations on the surface of Mars

Following an ESA preliminary study on the possible areas of European participation in the future international exploration of Mars and an ESA call for ideas of new missions, MARSNET, a network of small surface stations, was selected for further in-depth scientific and technical assessment studies as a potential European contribution to such exploration. Subsequently, the MARSNET phase A studies started in the autumn of 1991. The industrial kickoff took place in early January 1992, following the tender evaluation and the decision to select the Aerospatiale-led consortium including Dornier, Alcatel, Laben, and Etca to perform the industrial studies. The phase A studies ended in early 1993. However, critical items such as an instrument deployment device continue to be studied in the framework of ESA's Technology Research Program. The MARSNET mission consists of a network of three semihard landers to be placed on the Martian surface, several thousand kilometers apart, thus defining a regional/global seismological and meteorological network in the Tharsis region. The small stations would be targeted for landing at scientifically interesting sites in this region of Mars, which is the most likely area to still show tectonic activity; this would allow the seismometers to acquire data for the determination of the internal structure of the planet. Landing site geology and geochemistry will also be studied.

Chicarro, A. F.↗

Neural network controller development for a magnetically suspended flywheel energy storage system

A neural network controller has been developed to accommodate disturbances and nonlinearities and improve the robustness of a magnetically suspended flywheel energy storage system. The controller is trained using the back propagation-through-time technique incorporated with a time-averaging scheme. The resulting nonlinear neural network controller improves system performance by adapting flywheel stiffness and damping based on operating speed. In addition, a hybrid multi-layered neural network controller is developed off-line which is capable of improving system performance even further. All of the research presented in this paper was implemented via a magnetic bearing computer simulation. However, careful attention was paid to developing a practical methodology which will make future application to the actual bearing system fairly straightforward.

Fittro, Roger L.↗

Neural Network for Positioning Space Station Solar Arrays

As a shuttle approaches the Space Station Freedom for a rendezvous, the shuttle's reaction control jet firings pose a risk of excessive plume impingement loads on Freedom solar arrays. The current solution to this problem, in which the arrays are locked in a feathered position prior to the approach, may be neither accurate nor robust, and is also expensive. An alternative solution is proposed here: the active control of Freedom's beta gimbals during the approach, positioning the arrays dynamically in such a way that they remain feathered relative to the shuttle jet most likely to cause an impingement load. An artificial neural network is proposed as a means of determining the gimbal angles that would drive plume angle of attack to zero. Such a network would be both accurate and robust, and could be less expensive to implement than the current solution. A network was trained via backpropagation, and results, which compare favorably to the current solution as well as to some other alternatives, are presented. Other training options are currently being evaluated.

Graham, Ronald E.↗

The GPS Topex/Poseidon precise orbit determination experiment - Implications for design of GPS global networks

Topex/Poseidon, a cooperative satellite mission between United States and France, aims to determine global ocean circulation patterns and to study their influence on world climate through precise measurements of sea surface height above the geoid with an on-board altimeter. To achieve the mission science aims, a goal of 13-cm orbit altitude accuracy was set. Topex/Poseidon includes a Global Positioning System (GPS) precise orbit determination (POD) system that has now demonstrated altitude accuracy better than 5 cm. The GPS POD system includes an on-board GPS receiver and a 6-station GPS global tracking network. This paper reviews early GPS results and discusses multi-mission capabilities available from a future enhanced global GPS network, which would provide ground-based geodetic and atmospheric calibrations needed for NASA deep space missions while also supplying tracking data for future low Earth orbiters. Benefits of the enhanced global GPS network include lower operations costs for deep space tracking and many scientific and societal benefits from the low Earth orbiter missions, including improved understanding of ocean circulation, ocean-weather interactions, the El Nino effect, the Earth thermal balance, and weather forecasting.

Lindqwister, Ulf J.↗

The proposed HDTV schemes and the NASA network

Results of the simulation of high definition television (HDTV) techniques in the context of their application to transmit HDTV sequences over the NASA network are presented. Various tradeoffs involved in selecting the different services available on the NASA network are discussed. The possibility of transmitting an HDTV-like signal over the CCSDS network is investigated. Some suitable approaches are suggested.

Chen, Y. C.↗

Neural network prediction of aluminum-lithium weld strengths from acoustic emission amplitude data

AE flaw growth activity was monitored in aluminum-lithium weld specimens from the onset of tensile loading to failure. Data on actual ultimate strengths together with AE data from the beginning of loading up to 25 percent of the expected ultimate strength were used to train a backpropagation neural network to predict ultimate strengths. Architecturally, the fully interconnected network consisted of an input layer for the AE amplitude data, a hidden layer to accommodate failure mechanism mapping, and an output layer for ultimate strength prediction. The trained network was then applied to the prediction of ultimate strengths in the remaining six specimens. The worst case prediction error was found to be +2.6 percent.

Hill, Eric V. K.↗

Fractal characteristics of ozonometric network

The fractal (correlation) dimensions are calculated which characterize the distribution of stations in the ground-based total ozone measuring network and the distribution of nodes in a latitude-longitude grid. The dimension of the ground-based ozonometric network equals 1.67 +/- 0.1 with an appropriate scaling in the 60 to 400 km range. For the latitude-longitude grid two scaling regimes are revealed. One regime, with the dimension somewhat greater than one, is peculiar to smaller scales and limited from a larger scale by the latitudinal resolution of the grid. Another scaling regime, with the dimension equal 1.84, ranges up to 15,000 km scale. The fact that the dimension of a measuring network is less than two possesses problems in observing sparse phenomena. This has to have important consequences for ozone statistics.

Gruzdev, Alexander N.↗