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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 883 records · Page 49

Intersatellite Link (ISL) application to commercial communications satellites. Volume 2: Technical final report

Intersatellite Link (ISL) applications can improve and expand communication satellite services in a number of ways. As the demand for orbital slots within prime regions of the geostationary arc increases, attention is being focused on ISLs as a method to utilize this resource more efficiently and circumvent saturation. Various GEO-to-GEO applications were determined that provide potential benefits over existing communication systems. A set of criteria was developed to assess the potential applications. Intersatellite link models, network system architectures, and payload configurations were developed. For each of the chosen ISL applications, ISL versus non-ISL satellite systems architectures were derived. Both microwave and optical ISL implementation approaches were evaluated for payload sizing and cost analysis. The technological availability for ISL implementations was assessed. Critical subsystems technology areas were identified, and an estamate of the schedule and cost to advance the technology to the requiered state of readiness was made.

Young, S. Lee↗

Network protocols for real-time applications

The Fiber Distributed Data Interface (FDDI) and the SAE AE-9B High Speed Ring Bus (HSRB) are emerging standards for high-performance token ring local area networks. FDDI was designed to be a general-purpose high-performance network. HSRB was designed specifically for military real-time applications. A workshop was conducted at NASA Ames Research Center in January, 1987 to compare and contrast these protocols with respect to their ability to support real-time applications. This report summarizes workshop presentations and includes an independent comparison of the two protocols. A conclusion reached at the workshop was that current protocols for the upper layers of the Open Systems Interconnection (OSI) network model are inadequate for real-time applications.

Johnson, Marjory J.↗

Electronic hardware implementations of neutral networks

This paper examines some of the present work on the development of electronic neural network hardware. In particular, the investigations currently under way at JPL on neural network hardware implementations based on custom VLSI technology, novel thin film materials, and an analog-digital hybrid architecture are reviewed. The availability of such hardware will greatly benefit and enhance the present intense research effort on the potential computational capabilities of highly parallel systems based on neural network models.

Thakoor, A. P.↗

Simulated annealing in networks for computing possible arrangements for red and green cones

Attention is given to network models in which each of the cones of the retina is given a provisional color at random, and then the cones are allowed to determine the colors of their neighbors through an iterative process. A symmetric-structure spin-glass model has allowed arrays to be generated from completely random arrangements of red and green to arrays with approximately as much disorder as the parafoveal cones. Simulated annealing has also been added to the process in an attempt to generate color arrangements with greater regularity and hence more revealing moirepatterns than than the arrangements yielded by quenched spin-glass processes. Attention is given to the perceptual implications of these results.

Ahumada, Albert J., Jr.↗

Applications of concurrent neuromorphic algorithms for autonomous robots

This article provides an overview of studies at the Oak Ridge National Laboratory (ORNL) of neural networks running on parallel machines applied to the problems of autonomous robotics. The first section provides the motivation for our work in autonomous robotics and introduces the computational hardware in use. Section 2 presents two theorems concerning the storage capacity and stability of neural networks. Section 3 presents a novel load-balancing algorithm implemented with a neural network. Section 4 introduces the robotics test bed now in place. Section 5 concerns navigation issues in the test-bed system. Finally, Section 6 presents a frequency-coded network model and shows how Darwinian techniques are applied to issues of parameter optimization and on-line design.

Barhen, J.↗

Binary synaptic connections based on memory switching in a-Si:H for artificial neural networks

A scheme for nonvolatile associative electronic memory storage with high information storage density is proposed which is based on neural network models and which uses a matrix of two-terminal passive interconnections (synapses). It is noted that the massive parallelism in the architecture would require the ON state of a synaptic connection to be unusually weak (highly resistive). Memory switching using a-Si:H along with ballast resistors patterned from amorphous Ge-metal alloys is investigated for a binary programmable read only memory matrix. The fabrication of a 1600 synapse test array of uniform connection strengths and a-Si:H switching elements is discussed.

Thakoor, A. P.↗

Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks

Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.

Mclauchlan, Robert A.↗

Performance analysis of fault-tolerant systems in parallel execution of conversations

The execution overhead inherent in the conversation scheme, which is a scheme for realizing fault-tolerant cooperating processes free of the domino effect, is analyzed. Multiprocessor/multicomputer systems capable of parallel execution of conversation components are considered and a queuing network model of such systems is adopted. Based on the queuing model, various performance indicators, including system throughput, average number of processors idling inside a conversation due to the synchronization required, and average time spent in the conversation, have been evaluated numerically for several application environments. The numeric results are discussed and several essential performance characteristics of the conversation scheme are derived. For example, when the number of participant processes is not large, say less than six, the system performance is highly affected by the synchronization required on the processes in a conversation, and not so much by the probability of acceptance-test failure.

Kim, K. H.↗

Performance impacts of look-ahead execution in the conversation scheme

The look-ahead execution approach, which allows participant processes that exist early to exit from a conversation before other participants finish their conversation activities, is presented here as a fundamental approach to reducing the synchronization overhead. Queuing network models are developed for systems operating under the basic conversation execution scheme and systems operating under the look-ahead execution scheme. Based on the models, various performance indicators such as the system throughput, the average number of processors idling inside a conversation due to the synchronization required, and the average time spent in conversation are evaluated numerically for different application environments. The results provide insights into the extent of benefits provided by the look-ahead execution approach.

Kim, K. H.↗

Manganese oxide microswitch for electronic memory based on neural networks

A solid-state, resistance tailorable, programmable-once, binary, nonvolatile memory switch based on manganese oxide thin films is reported. MnO(x) exhibits irreversible memory switching from conducting (on) to insulating (off) state, with the off and on resistance ratio of greater than 10,000. The switching mechanism is current-triggered chemical transformation of a conductive MnO(2-Delta) to an insulating Mn2O3 state. The energy required for switching is of the order of 4-20 nJ/sq micron. The low switching energy, stability of the on and off states, and tailorability of the on state resistance make these microswitches well suited as programmable binary synapses in electronic associative memories based on neural network models.

Ramesham, R.↗

Adjustable impedance, force feedback and command language aids for telerobotics (parts 1-4 of an 8-part MIT progress report)

Projects recently completed or in progress at MIT Man-Machine Systems Laboratory are summarized. (1) A 2-part impedance network model of a single degree of freedom remote manipulation system is presented in which a human operator at the master port interacts with a task object at the slave port in a remote location is presented. (2) The extension of the predictor concept to include force feedback and dynamic modeling of the manipulator and the environment is addressed. (3) A system was constructed to infer intent from the operator's commands and the teleoperation context, and generalize this information to interpret future commands. (4) A command language system is being designed that is robust, easy to learn, and has more natural man-machine communication. A general telerobot problem selected as an important command language context is finding a collision-free path for a robot.

Sheridan, Thomas B.↗

Auto- and hetero-associative memory using a 2-D optical logic gate

An optical associative memory system suitable for both auto- and hetero-associative recall is demonstrated. This system utilizes Hamming distance as the similarity measure between a binary input and a memory image with the aid of a two-dimensional optical EXCLUSIVE OR (XOR) gate and a parallel electronics comparator module. Based on the Hamming distance measurement, this optical associative memory performs a nearest neighbor search and the result is displayed in the output plane in real-time. This optical associative memory is fast and noniterative and produces no output spurious states as compared with that of the Hopfield neural network model.

Chao, Tien-Hsin↗

Spatial light modulators and applications III; Proceedings of the Meeting, San Diego, CA, Aug. 7, 8, 1989

Recent advances in the technology and applications of spatial light modulators (SLMs) are discussed in review essays by leading experts. Topics addressed include materials for SLMs, SLM devices and device technology, applications to optical data processing, and applications to artificial neural networks. Particular attention is given to nonlinear optical polymers, liquid crystals, magnetooptic SLMs, multiple-quantum-well SLMs, deformable-mirror SLMs, three-dimensional optical memories, applications of photorefractive devices to optical computing, photonic neurocomputers and learning machines, holographic associative memories, SLMs as parallel memories for optoelectronic neural networks, and coherent-optics implementations of neural-network models.

Efron, Uzi↗

An architecture for designing fuzzy logic controllers using neural networks

Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

Berenji, Hamid R.↗

Architecture for Survivable System Processing (ASSP)

The Architecture for Survivable System Processing (ASSP) Program is a multi-phase effort to implement Department of Defense (DOD) and commercially developed high-tech hardware, software, and architectures for reliable space avionics and ground based systems. System configuration options provide processing capabilities to address Time Dependent Processing (TDP), Object Dependent Processing (ODP), and Mission Dependent Processing (MDP) requirements through Open System Architecture (OSA) alternatives that allow for the enhancement, incorporation, and capitalization of a broad range of development assets. High technology developments in hardware, software, and networking models, address technology challenges of long processor life times, fault tolerance, reliability, throughput, memories, radiation hardening, size, weight, power (SWAP) and security. Hardware and software design, development, and implementation focus on the interconnectivity/interoperability of an open system architecture and is being developed to apply new technology into practical OSA components. To insure for widely acceptable architecture capable of interfacing with various commercial and military components, this program provides for regular interactions with standardization working groups (e.g.) the International Standards Organization (ISO), American National Standards Institute (ANSI), Society of Automotive Engineers (SAE), and Institute of Electrical and Electronic Engineers (IEEE). Selection of a viable open architecture is based on the widely accepted standards that implement the ISO/OSI Reference Model.

Wood, Richard J.↗

Real-time antenna fault diagnosis experiments at DSS 13

Experimental results obtained when a previously described fault diagnosis system was run online in real time at the 34-m beam waveguide antenna at Deep Space Station (DSS) 13 are described. Experimental conditions and the quality of results are described. A neural network model and a maximum-likelihood Gaussian classifier are compared with and without a Markov component to model temporal context. At the rate of a state update every 6.4 seconds, over a period of roughly 1 hour, the neural-Markov system had zero errors (incorrect state estimates) while monitoring both faulty and normal operations. The overall results indicate that the neural-Markov combination is the most accurate model and has significant practical potential.

Mellstrom, J.↗

Artificial neural networks and approximate reasoning for intelligent control in space

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Berenji, Hamid R.↗

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

Sartori, Michael A.↗