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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Shape memory alloys: New materials for future engineering

Shape memory is a new material property. An alloy which experiences relative severe plastic deformation resumes its original shape again after heating by 10 to 100 C. Besides simple shape memory, in similar alloys there is the second effect where the change in shape is caused exclusively by little temperature change. In pseudo-elasticity, the alloy exhibits a rubber-like behavior, i.e., large, reversible deformation at little change in tension. Beta Cu and beta NiTi alloys have been used in practice. The probability is that soon alloys based on Fe will become available. Recently increasing applications for this alloy were found in various areas of technology, even medical technology. A review with 24 references is given, including properties, production, applications and fundamental principles of the shape memory effect.

Hornbogen, E.↗
NASA NTRS1987

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.↗
NASA NTRS1989

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.↗
NASA NTRS1990

Programmable Analog Memory Resistors For Electronic Neural Networks

Electrical resistance of new solid-state device altered repeatedly by suitable control signals, yet remains at steady value when control signal removed. Resistance set at low value ("on" state), high value ("off" state), or at any convenient intermediate value and left there until new value desired. Circuits of this type particularly useful in nonvolatile, associative electronic memories based on models of neural networks. Such programmable analog memory resistors ideally suited as synaptic interconnects in "self-learning" neural nets. Operation of device depends on electrochromic property of WO3, which when pure is insulator. Potential uses include nonvolatile, erasable, electronically programmable read-only memories.

Ramesham, Rajeshuni↗
NASA NTRS1990

Programmable Direct-Memory-Access Controller

Proposed programmable direct-memory-access controller (DMAC) operates with computer systems of 32000 series, which have 32-bit data buses and use addresses of 24 (or potentially 32) bits. Controller functions with or without help of central processing unit (CPU) and starts itself. Includes such advanced features as ability to compare two blocks of memory for equality and to search block of memory for specific value. Made as single very-large-scale integrated-circuit chip.

Hendry, David F.↗
NASA NTRS1990

32-Bit-Wide Memory Tolerates Failures

Electronic memory system of 32-bit words corrects bit errors caused by some common type of failures - even failure of entire 4-bit-wide random-access-memory (RAM) chip. Detects failure of two such chips, so user warned that ouput of memory may contain errors. Includes eight 4-bit-wide DRAM's configured so each bit of each DRAM assigned to different one of four parallel 8-bit words. Each DRAM contributes only 1 bit to each 8-bit word.

Buskirk, Glenn A.↗
NASA NTRS1988

Sparse distributed memory

Theoretical models of the human brain and proposed neural-network computers are developed analytically. Chapters are devoted to the mathematical foundations, background material from computer science, the theory of idealized neurons, neurons as address decoders, and the search of memory for the best match. Consideration is given to sparse memory, distributed storage, the storage and retrieval of sequences, the construction of distributed memory, and the organization of an autonomous learning system.

Kanerva, Pentti↗
NASA NTRS1989

Electronic shift register memory based on molecular electron-transfer reactions

The design of a shift register memory at the molecular level is described in detail. The memory elements are based on a chain of electron-transfer molecules incorporated on a very large scale integrated (VLSI) substrate, and the information is shifted by photoinduced electron-transfer reactions. The design requirements for such a system are discussed, and several realistic strategies for synthesizing these systems are presented. The immediate advantage of such a hybrid molecular/VLSI device would arise from the possible information storage density. The prospect of considerable savings of energy per bit processed also exists. This molecular shift register memory element design solves the conceptual problems associated with integrating molecular size components with larger (micron) size features on a chip.

Hopfield, J. J.↗
NASA NTRS1991

Conditional Probability And The Sparse Distributed Memory

Report presents conditional-probability interpretation of Kanerva's sparse distributed memory (SDM). SDM is conceptual digital electronic memory in which addresses chosen sparsely in space of many dimensions and content of memory at each address positive or negative integer written (incremented or decremented) or read according to special rules. Contents of SDM constitute Monte Carlo approximation to multidimensional conditional-probability integral.

Anderson, Charles H.↗
NASA NTRS1991

Associative-Memory Array Of Optical Logic Gates

Experimental optical associative-memory apparatus measures similarity or dissimilarity between input binary image and each of M binary images in memory. Uses Hamming distance as measure of dissimilarity, determines which (if any) of memory images closely or most closely resembles input image. Indicates this match by displaying image (e.g., recognized image or symbol, word, number, or other substitute image) in real time on output plane.

Chao, Tien-Hsin↗
NASA NTRS1990

Programming distributed memory architectures using Kali

Programming nonshared memory systems is more difficult than programming shared memory systems, in part because of the relatively low level of current programming environments for such machines. A new programming environment is presented, Kali, which provides a global name space and allows direct access to remote data values. In order to retain efficiency, Kali provides a system on annotations, allowing the user to control those aspects of the program critical to performance, such as data distribution and load balancing. The primitives and constructs provided by the language is described, and some of the issues raised in translating a Kali program for execution on distributed memory systems are also discussed.

Mehrotra, Piyush↗
NASA NTRS1991

Shared versus distributed memory multiprocessors

The question of whether multiprocessors should have shared or distributed memory has attracted a great deal of attention. Some researchers argue strongly for building distributed memory machines, while others argue just as strongly for programming shared memory multiprocessors. A great deal of research is underway on both types of parallel systems. Special emphasis is placed on systems with a very large number of processors for computation intensive tasks and considers research and implementation trends. It appears that the two types of systems will likely converge to a common form for large scale multiprocessors.

Jordan, Harry F.↗
NASA NTRS1991

Efficient packing of patterns in sparse distributed memory by selective weighting of input bits

When a set of patterns is stored in a distributed memory, any given storage location participates in the storage of many patterns. From the perspective of any one stored pattern, the other patterns act as noise, and such noise limits the memory's storage capacity. The more similar the retrieval cues for two patterns are, the more the patterns interfere with each other in memory, and the harder it is to separate them on retrieval. A method is described of weighting the retrieval cues to reduce such interference and thus to improve the separability of patterns that have similar cues.

Kanerva, Pentti↗
NASA NTRS1991

Differential memory in the earth's magnetotail

The process of 'differential memory' in the earth's magnetotail is studied in the framework of the modified Harris magnetotail geometry. It is verified that differential memory can generate non-Maxwellian features in the modified Harris field model. The time scales and the potentially observable distribution functions associated with the process of differential memory are investigated, and it is shown that non-Maxwelllian distributions can evolve as a test particle response to distribution function boundary conditions in a Harris field magnetotail model. The non-Maxwellian features which arise from distribution function mapping have definite time scales associated with them, which are generally shorter than the earthward convection time scale but longer than the typical Alfven crossing time.

Burkhart, G. R.↗
NASA NTRS1992

Compact Spare-Row Decoder For Computer Memory

Spare-row memory-address-decoder circuit commanded to address ninth row in computer memory instead of addressing one of eight others it would address normally. Variants used to construct small, highly reliable computers. Spare-row decoder offers advantages of compactness, efficiency, and performance. Requires only 12.5 percent memory overhead. System equipped with spare-row decoder requires less glue logic and exhibits greater through-put. Applications include computers in Hitchhiker Central Unit embedded computer on Cassini spacecraft. Concept of circuit applicable to most flight computer systems.

Katz, Richard B.↗
NASA NTRS1992

Memory Network For Distributed Data Processors

Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.

Bolen, David↗
NASA NTRS1991

Total recall in distributive associative memories

Iterative error correction of asymptotically large associative memories is equivalent to a one-step learning rule. This rule is the inverse of the activation function of the memory. Spectral representations of nonlinear activation functions are used to obtain the inverse in closed form for Sparse Distributed Memory, Selected-Coordinate Design, and Radial Basis Functions.

Danforth, Douglas G.↗