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All sourcesNASA NTRSDOE OSTI
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

Solid-state thin-film memistor for electronic neural networks

This paper reports on a tungsten-oxide-based, nonvolatile, electrically reprogrammable, variable resistance device as an analog synaptic memory connection for electronic neural networks. A voltage controlled, reversible injection of H(+) ions in electrochromic thin films of WO3 is utilized to modulate its resistance. A hygroscopic thin film of Cr2O3 is the source of H(+) ions. The resistance of the device can be tailored and stabilized over a wide dynamic range (about 4 orders of magnitude), and the programming speed is modulated by the control voltage. The suitability of such a device in terms of its response speed, reversibility, stability, and cyclability for its use in electronic neural networks is discussed.

Thakoor, S.↗
NASA NTRS1990

Solid-state reprogrammable analog resistive devices for electronic neural networks

The fabrication and performance of WO3-based, solid-state, three-terminal device configurations as programmable analog memory elements are reported. These transistorlike device structures exhibit good resistance progammability with a remarkable resolution of a few percent of the resistive strength over a four orders of magnitude dynamic range. The most critical component of these devices is an insulating layer between the active WO3 and the cation donor layer. The progamming characteristics and operation mechanisms of the device are described, and probable reaction mechanisms critical to the device stability are discussed.

Ramesham, R.↗
NASA NTRS1992

Analog hardware for delta-backpropagation neural networks

This is a fully parallel analog backpropagation learning processor which comprises a plurality of programmable resistive memory elements serving as synapse connections whose values can be weighted during learning with buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in a plurality of neuron layers in accordance with delta-backpropagation algorithms modified so as to control weight changes due to circuit drift.

Eberhardt, Silvio P.↗
NASA NTRS1991

Ferroelectric Memory Capacitors For Neural Networks

Thin-film ferroelectric capacitors proposed as nonvolatile analog memory devices. Intended primarily for use as synaptic connections in electronic neural networks. Connection strengths (synaptic weights) stored as nonlinear remanent polarizations of ferroelectric films. Ferroelectric memory and interrogation capacitors combined into memory devices in vertical or lateral configurations. Photoconductive layer modulated by light provides variable resistance to alter bias signal applied to memory capacitor. Features include nondestructive readout, simplicity, and resistance to ionizing radiation. Interrogated without destroying stored analog data. Also amenable to very-large-scale integration. Allows use of ac coupling, eliminating errors caused by dc offsets in amplifier circuits of neural networks.

Thakoor, Sarita↗
NASA NTRS1991

Stacked-Gate FET's For Analog Memory Elements

Three-terminal, double-stacked-gate field-effect transistor (FET), developed as analog memory element. Particularly suited for use as synapse with variable connection strength in electronic neural network. Provides programmable, nonvolatile resistive connection, somewhat in manner of porous-gate FET described in "Porous-Floating-Gate Field-Effect Transistor" (NPO-17532). Resembles commercial erasable programmable read-only memory (EPROM) device, except for thickness of layers of silicon dioxide electrically isolating gates. Either p-channel or n-channel device.

Thakoor, Anilkumar P.↗
NASA NTRS1994

Integrated, nonvolatile, high-speed analog random access memory

This invention provides an integrated, non-volatile, high-speed random access memory. A magnetically switchable ferromagnetic or ferrimagnetic layer is sandwiched between an electrical conductor which provides the ability to magnetize the magnetically switchable layer and a magneto resistive or Hall effect material which allows sensing the magnetic field which emanates from the magnetization of the magnetically switchable layer. By using this integrated three-layer form, the writing process, which is controlled by the conductor, is separated from the storage medium in the magnetic layer and from the readback process which is controlled by the magnetoresistive layer. A circuit for implementing the memory in CMOS or the like is disclosed.

Katti, Romney R.↗
NASA NTRS1990

Analog Delta-Back-Propagation Neural-Network Circuitry

Changes in synapse weights due to circuit drifts suppressed. Proposed fully parallel analog version of electronic neural-network processor based on delta-back-propagation algorithm. Processor able to "learn" when provided with suitable combinations of inputs and enforced outputs. Includes programmable resistive memory elements (corresponding to synapses), conductances (synapse weights) adjusted during learning. Buffer amplifiers, summing circuits, and sample-and-hold circuits arranged in layers of electronic neurons in accordance with delta-back-propagation algorithm.

Eberhart, Silvio↗
NASA NTRS1974

The Ranicon - A resistive anode image converter

A versatile photon and charged particle imaging system is described. The Ranicon employs a microchannel electron multiplier plate to convert each detected event into a charge signal. This charge pulse is proximity-focused onto a large-area resistive anode plate equipped with pickup electrodes on its edges. Each event is located electronically by the ratios of the charges collected at the edges or by the differences of the signals' risetimes. One- or two-dimensional pictures are built up by storing events digitally (e.g., a core memory) or in analog form (e.g., a storage oscilloscope). Compact laboratory models have been constructed and tested. Operating characteristics, applications, limitations, and advantages of the Ranicon are discussed.

Lampton, M.↗
NASA NTRS2009

Electrically Variable or Programmable Nonvolatile Capacitors

Electrically variable or programmable capacitors based on the unique properties of thin perovskite films are undergoing development. These capacitors show promise of overcoming two important deficiencies of prior electrically programmable capacitors: Unlike in the case of varactors, it is not necessary to supply power continuously to make these capacitors retain their capacitance values. Hence, these capacitors may prove useful as components of nonvolatile analog and digital electronic memories. Unlike in the case of ferroelectric capacitors, it is possible to measure the capacitance values of these capacitors without changing the values. In other words, whereas readout of ferroelectric capacitors is destructive, readout of these capacitors can be nondestructive. A capacitor of this type is a simple two terminal device. It includes a thin film of a suitable perovskite as the dielectric layer, sandwiched between two metal or metal oxide electrodes (for example, see Figure 1). The utility of this device as a variable capacitor is based on a phenomenon, known as electrical-pulse-induced capacitance (EPIC), that is observed in thin perovskite films and especially in those thin perovskite films that exhibit the colossal magnetoresistive (CMR) effect. In EPIC, the application of one or more electrical pulses that exceed a threshold magnitude (typically somewhat less than 1 V) gives rise to a nonvolatile change in capacitance. The change in capacitance depends on the magnitude duration, polarity, and number of pulses. It is not necessary to apply a magnetic field or to cool the device below (or heat it above) room temperature to obtain EPIC. Examples of suitable CMR perovskites include Pr(1-x)Ca(x)MnO3, La(1-x)S-r(x)MnO3,and Nb(1-x)Ca(x)MnO3. Figure 2 is a block diagram showing an EPIC capacitor connected to a circuit that can vary the capacitance, measure the capacitance, and/or measure the resistance of the capacitor.

Shangqing, Liu↗