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NASA NTRS1992

Extrapolation limitations of multilayer feedforward neural networks

The limitations of backpropagation used as a function extrapolator were investigated. Four common functions were used to investigate the network's extrapolation capability. The purpose of the experiment was to determine whether neural networks are capable of extrapolation and, if so, to determine the range for which networks can extrapolate. The authors show that neural networks cannot extrapolate and offer an explanation to support this result.

Haley, Pamela J.↗

NASA NTRS1992

Neural network error correction for solving coupled ordinary differential equations

A neural network is presented to learn errors generated by a numerical algorithm for solving coupled nonlinear differential equations. The method is based on using a neural network to correctly learn the error generated by, for example, Runge-Kutta on a model molecular dynamics (MD) problem. The neural network programs used in this study were developed by NASA. Comparisons are made for training the neural network using backpropagation and a new method which was found to converge with fewer iterations. The neural net programs, the MD model and the calculations are discussed.

Shelton, R. O.↗

NASA NTRS1992

High-performance network and channel based storage

In the traditional mainframe-centered view of a computer system, storage devices are coupled to the system through complex hardware subsystems called I/O channels. With the dramatic shift toward workstation-based computing, and its associated client/server model of computation, storage facilities are now found attached to file servers and distributed throughout the network. In this paper, we discuss the underlying technology trends that are leading to high-performance network-based storage, namely advances in networks, storage devices, and I/O controller and server architectures. We review several commercial systems and research prototypes that are leading to a new approach to high-performance computing based on network-attached storage.

Katz, Randy H.↗

NASA NTRS1992

Feature selection for neural networks using Parzen density estimator

A feature selection method for neural networks is proposed using the Parzen density estimator. A new feature set is selected using the decision boundary feature selection algorithm. The selected feature set is then used to train a neural network. Using a reduced feature set, an attempt is made to reduce the training time of the neural network and obtain a simpler neural network, which further reduces the classification time for test data.

Lee, Chulhee↗

NASA NTRS1992

Classification of remotely sensed data using OCR-inspired neural network techniques

Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

Kiang, Richard K.↗

NASA NTRS1993

Classification of multispectral image data by the Binary Diamond neural network and by nonparametric, pixel-by-pixel methods

The classification of multispectral image data obtained from satellites has become an important tool for generating ground cover maps. This study deals with the application of nonparametric pixel-by-pixel classification methods in the classification of pixels, based on their multispectral data. A new neural network, the Binary Diamond, is introduced, and its performance is compared with a nearest neighbor algorithm and a back-propagation network. The Binary Diamond is a multilayer, feed-forward neural network, which learns from examples in unsupervised, 'one-shot' mode. It recruits its neurons according to the actual training set, as it learns. The comparisons of the algorithms were done by using a realistic data base, consisting of approximately 90,000 Landsat 4 Thematic Mapper pixels. The Binary Diamond and the nearest neighbor performances were close, with some advantages to the Binary Diamond. The performance of the back-propagation network lagged behind. An efficient nearest neighbor algorithm, the binned nearest neighbor, is described. Ways for improving the performances, such as merging categories, and analyzing nonboundary pixels, are addressed and evaluated.

Salu, Yehuda↗

NASA NTRS1993

Dynamics of the solar chromosphere. I - Long-period network oscillations

We analyze differences in solar oscillations between the chromospheric network and internetwork regions from a 1 hr sequence of spectrograms of a quiet region near disk center. The spectrograms contain Ca II H, Ca I 422.7 nm, and various Fe I blends in the Ca II H wing. They permit vertical tracing of oscillations throughout the photosphere and into the low chromosphere. We find that the rms amplitude of Ca II H line center Doppler fluctuations is about 1.5 km/s for both network and internetwork, but that the character of the oscillations differs markedly in these two regions. Within internetwork areas the chromospheric velocity power spectrum is dominated by oscillations with frequencies at and above the acoustic cutoff frequency. They are well correlated with the oscillations in the underlying photosphere, but they are much reduced in the network. In contrast, the network Ca II H line center velocity and intensity power spectra are dominated by low-frequency oscillations with periods of 5-20 min. Their signature is much clearer in our Ca II H line center measurements than in previously used diagnostics which are contaminated by signals from deeper layers. We find that these long-period oscillations are not correlated with underlying photospheric disturbances, and we discuss their nature.

Lites, B. W.↗

NASA NTRS1994

Software For Management Of A Packet-Radio Network

Network-management software assists in planning, monitoring, and controlling resources of Datalink network. Packet-message network featuring time-division multiple access, frequency and spatial diversity, and dynamic tree-structured routing scheme. Developed for communication between central control station on ground and instrumented aircraft flying over test range. Aircraft derives navigational data from satellites of Global Positioning System, and primary function of Datalink network feeding GPS position data from participating aircraft into control center in real time.

Smyth, Patrick J.↗

NASA NTRS1994

Optical-Correlator Neural Network Based On Neocognitron

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Chao, Tien-Hsin↗

NASA NTRS1994

High-Speed Optical Wide-Area Data-Communication Network

Proposed fiber-optic wide-area network (WAN) for digital communication balances input and output flows of data with its internal capacity by routing traffic via dynamically interconnected routing planes. Data transmitted optically through network by wavelength-division multiplexing in synchronous or asynchronous packets. WAN implemented with currently available technology. Network is multiple-ring cyclic shuffle exchange network ensuring traffic reaches its destination with minimum number of hops.

Monacos, Steve P.↗

NASA NTRS1993

Distributed simulation using a real-time shared memory network

The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

Simon, Donald L.↗

NASA NTRS1993

Functional approximation using artificial neural networks in structural mechanics

The artificial neural networks (ANN) methodology is an outgrowth of research in artificial intelligence. In this study, the feed-forward network model that was proposed by Rumelhart, Hinton, and Williams was applied to the mapping of functions that are encountered in structural mechanics problems. Several different network configurations were chosen to train the available data for problems in materials characterization and structural analysis of plates and shells. By using the recall process, the accuracy of these trained networks was assessed.

Alam, Javed↗

NASA NTRS1993

Asynchronous transfer mode link performance over ground networks

The results of an experiment to determine the feasibility of using asynchronous transfer mode (ATM) technology to support advanced spacecraft missions that require high-rate ground communications and, in particular, full-motion video are reported. Potential nodes in such a ground network include Deep Space Network (DSN) antenna stations, the Jet Propulsion Laboratory, and a set of national and international end users. The experiment simulated a lunar microrover, lunar lander, the DSN ground communications system, and distributed science users. The users were equipped with video-capable workstations. A key feature was an optical fiber link between two high-performance workstations equipped with ATM interfaces. Video was also transmitted through JPL's institutional network to a user 8 km from the experiment. Variations in video depending on the networks and computers were observed, the results are reported.

Chow, E. T.↗

NASA NTRS1993

A neural-network approach to robotic control

An artificial neural-network paradigm for the control of robotic systems is presented. The approach is based on the Cerebellar Model Articulation Controller created by James Albus and incorporates several extensions. First, recognizing the essential structure of multibody equations of motion, two parallel modules are used that directly reflect the dynamical characteristics of multibody systems. Second, the architecture of the proposed network is imbued with a self-organizational capability which improves efficiency and accuracy. Also, the networks can be arranged in hierarchical fashion with each subsequent network providing finer and finer resolution.

Graham, D. P. W.↗

NASA NTRS1993

Computer networking at SLR stations

There are several existing communication methods to deliver data from the satellite laser ranging (SLR) station to the SLR data center and back: telephonmodem, telex, and computer networks. The SLR scientific community has been exploiting mainly INTERNET, BITNET/EARN, and SPAN. The total of 56 countries are connected to INTERNET and the number of nodes is exponentially growing. The computer networks mentioned above and others are connected through E-mail protocol. The scientific progress of SLR requires the increase of communication speed and the amount of the transmitted data. The TOPEX/POSEIDON test campaign required to deliver Quick Look data (1.7 kB/pass) from a SLR site to SLR data center within 8 hours and full rate data (up to 500 kB/pass) within 24 hours. We developed networking for the remote SLR station in Helwan, Egypt. The reliable scheme for data delivery consists of: compression of MERIT2 format (up to 89 percent), encoding to ASCII Me (files); and e-mail sending from SLR station--e-mail receiving, decoding, and decompression at the center. We do propose to use the ZIP method for compression/decompression and the UUCODE method for ASCII encoding/decoding. This method will be useful for stations connected via telephonemodems or commercial networks. The electronics delivery could solve the problem of the too late receiving of the FR data by SLR data center.

Novotny, Antonin↗

NASA NTRS1991

Pulse-firing winner-take-all networks

Winner-take-all (WTA) neural networks using pulse-firing processing elements are introduced. In the pulse-firing WTA (PWTA) networks described, input and activation signal shunting is controlled by one shared lateral inhibition signal. This organization yields an O(n) area complexity that is convenient for integrated circuit implementation. Appropriately specified network parameters allow for the accurate continuous evaluation of inputs using a signal representation compatible with established pulse-firing neural network implementations.

Meador, Jack L.↗

NASA NTRS1993

The Test Analysis Retrieval System (TARS): Meeting the challenges of the network's test processes

The Networks Systems Test Section (GSFC 531.4) is responsible for managing a variety of engineering and operational tests used to assess the status of the Network elements relative to readiness certification for new and ongoing mission support and for performance trending. To conduct analysis of data collected during these tests, to disseminate and share the information, and to catalog and create reports based on the analysis is currently a cumbersome and inefficient task due primarily to the manual handling of paper products and the inability to easily exchange information between the various Networks elements. The Test Analysis and Retrieval System (TARS) is being implemented to promote concise data analysis, intelligible reporting of test results, to minimize test duplication by fostering a broad sharing of test data, and perhaps most importantly, to provide significantly improved response to the Network's internal and external customers. This paper outlines the intended application, architecture, and benefits of the TARS.

Stelmaszek, Robert L.↗

NASA NTRS1993

Using satellite communications for a mobile computer network

The topics discussed include the following: patrol car automation, mobile computer network, network requirements, network design overview, MCN mobile network software, MCN hub operation, mobile satellite software, hub satellite software, the benefits of patrol car automation, the benefits of satellite mobile computing, and national law enforcement satellite.

Wyman, Douglas J.↗