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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Kanerva's sparse distributed memory: An associative memory algorithm well-suited to the Connection Machine

The advent of the Connection Machine profoundly changes the world of supercomputers. The highly nontraditional architecture makes possible the exploration of algorithms that were impractical for standard Von Neumann architectures. Sparse distributed memory (SDM) is an example of such an algorithm. Sparse distributed memory is a particularly simple and elegant formulation for an associative memory. The foundations for sparse distributed memory are described, and some simple examples of using the memory are presented. The relationship of sparse distributed memory to three important computational systems is shown: random-access memory, neural networks, and the cerebellum of the brain. Finally, the implementation of the algorithm for sparse distributed memory on the Connection Machine is discussed.

Rogers, David↗
NASA NTRS1992

Experimental Optoelectronic Associative Memory

Optoelectronic associative memory responds to input image by displaying one of M remembered images. Which image to display determined by optoelectronic analog computation of resemblance between input image and each remembered image. Does not rely on precomputation and storage of outer-product synapse matrix. Size of memory needed to store and process images reduced.

Chao, Tien-Hsin↗
NASA NTRS1993

Optoelectronic associative memory

An associative optical memory including an input spatial light modulator (SLM) in the form of an edge enhanced liquid crystal light valve (LCLV) and a pair of memory SLM's in the form of liquid crystal televisions (LCTV's) forms a matrix array of an input image which is cross correlated with a matrix array of stored images. The correlation product is detected and nonlinearly amplified to illuminate a replica of the stored image array to select the stored image correlating with the input image. The LCLV is edge enhanced by reducing the bias frequency and voltage and rotating its orientation. The edge enhancement and nonlinearity of the photodetection improves the orthogonality of the stored image. The illumination of the replicate stored image provides a clean stored image, uncontaminated by the image comparison process.

Chao, Tien-Hsin↗
NASA NTRS1990

Automatic ground control point recognition with parallel associative memory

The basic principle of the associative memory is to match the unknown input pattern against a stored training set, and responding with the 'closest match' and the corresponding label. Generally, an associative memory system requires two preparatory steps: selecting attributes of the pattern class, and training the system by associating patterns with labels. Experimental results gained from using Parallel Associative Memory are presented. The primary concern is an automatic search for ground control points in aerial photographs. Synthetic patterns are tested followed by real data. The results are encouraging as a relatively high level of correct matches is reached.

Al-Tahir, Raid↗
NASA NTRS1991

Trinary Associative Memory Would Recognize Machine Parts

Trinary associative memory combines merits and overcomes major deficiencies of unipolar and bipolar logics by combining them in three-valued logic that reverts to unipolar or bipolar binary selectively, as needed to perform specific tasks. Advantage of associative memory: one obtains access to all parts of it simultaneously on basis of content, rather than address, of data. Consequently, used to exploit fully parallelism and speed of optical computing.

Liu, Hua-Kuang↗
NASA NTRS1995

Two Unipolar Terminal-Attractor-Based Associative Memories

Two unipolar mathematical models of electronic neural network functioning as terminal-attractor-based associative memory (TABAM) developed. Models comprise sets of equations describing interactions between time-varying inputs and outputs of neural-network memory, regarded as dynamical system. Simplifies design and operation of optoelectronic processor to implement TABAM performing associative recall of images. TABAM concept described in "Optoelectronic Terminal-Attractor-Based Associative Memory" (NPO-18790). Experimental optoelectronic apparatus that performed associative recall of binary images described in "Optoelectronic Inner-Product Neural Associative Memory" (NPO-18491).

Liu, Hua-Kuang↗
NASA NTRS1989

High density associative memory

A multi-layered, thin-film, digital memory having associative recall. There is a first memory matrix and a second memory matrix. Each memory matrix comprises, a first layer comprising a plurality of electrically separated row conductors; a second layer comprising a plurality of electrically separated column conductors intersecting but electrically separated from the row conductors; and, a plurality of resistance elements electrically connected between the row condutors and the column conductors at respective intersections of the row conductors and the column conductors, each resistance element comprising, in series, a first resistor of sufficiently high ohmage to conduct a sensible element current therethrough with virtually no heat-generating power consumption when a low voltage as employed in thin-film applications is applied thereacross and a second resistor of sufficiently high ohmage to conduct no sensible current therethrough when a low voltage as employed in thin-film applications is applied thereacross, the second resistor having the quality of breaking down to create a short therethrough upon the application of a breakdown level voltage across the first and second resistors.

Moopenn, Alexander W.↗
NASA NTRS1989

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↗
NASA NTRS1993

Unipolar terminal-attractor based neural associative memory with adaptive threshold

A unipolar terminal-attractor based neural associative memory (TABAM) system with adaptive threshold for perfect convergence is presented. By adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors for the purpose of reducing the spurious states in a Hopfield neural network for associative memory and using the inner product approach, perfect convergence and correct retrieval is achieved. Simulation is completed with a small number of stored states (M) and a small number of neurons (N) but a large M/N ratio. An experiment with optical exclusive-OR logic operation using LCTV SLMs shows the feasibility of optoelectronic implementation of the models. A complete inner-product TABAM is implemented using a PC for calculation of adaptive threshold values to achieve a unipolar TABAM (UIT) in the case where there is no crosstalk, and a crosstalk model (CRIT) in the case where crosstalk corrupts the desired state.

Liu, Hua-Kuang↗
NASA NTRS1996

Unipolar Terminal-Attractor Based Neural Associative Memory with Adaptive Threshold

A unipolar terminal-attractor based neural associative memory (TABAM) system with adaptive threshold for perfect convergence is presented. By adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states with terminal-attractors for the purpose of reducing the spurious states in a Hopfield neural network for associative memory and using the inner-product approach, perfect convergence and correct retrieval is achieved. Simulation is completed with a small number of stored states (M) and a small number of neurons (N) but a large M/N ratio. An experiment with optical exclusive-OR logic operation using LCTV SLMs shows the feasibility of optoelectronic implementation of the models. A complete inner-product TABAM is implemented using a PC for calculation of adaptive threshold values to achieve a unipolar TABAM (UIT) in the case where there is no crosstalk, and a crosstalk model (CRIT) in the case where crosstalk corrupts the desired state.

Liu, Hua-Kuang↗
NASA NTRS1992

Optical implementation of terminal-attractor-based associative memory

For the purpose of reducing the spurious states in a Hopfield neural net for associative memory, we invoke terminal attractors. In achieving the optical implementation of the terminal-attractor-based associative memory (TABAM) as described in this paper, we first prove the existence of the terminal-attractor model with binary neuron representation. We then present several one- and two-dimensional optical architectures for the TABAM. Finally, as an example, we experimentally demonstrate an inner-product optical neural model using liquid-crystal spatial light modulators with engineering approximations and discuss how to apply the inner-product model to build a two-dimensional parallel processing TABAM.

Liu, Hua-Kuang↗
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.↗
NASA NTRS1990

Identification of aerospace acoustic sources using sparse distributed associative memory

A pattern recognition system has been developed to classify five different aerospace acoustic sources. In this paper the performance of two new classifiers, an associative memory classifier and a neural network classifier, is compared to the performance of a previously designed system. Sources are classified using features calculated from the time and frequency domain. Each classifier undergoes a training period where it learns to classify sources correctly based on a set of known sources. After training the classifier is tested with unknown sources. Results show that over 96 percent of sources were identified correctly with the new associative memory classifier. The neural network classifier identified over 81 percent of the sources correctly.

Scott, E. A.↗
NASA NTRS1990

The optical implementation of inner product neural associative memory

A liquid-crystal TV spatial light modulator (LCTV SLM) input device and LCTV nonlinear thresholding element are presently used to accomplish an all-optical implementation of an inner-product neural associative memory. This architecture represents an alternative to the vector-matrix multiplication method of the Hopfield model, which is most often employed by neural network associative memory models. LCTV SLM experimental results are presented and discussed.

Liu, Hua-Kuang↗
NASA NTRS1989

Machine parts recognition using a trinary associative memory

The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.

Awwal, Abdul Ahad S.↗
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↗