United States of America As Represented by the Secretary of the Air Force

Garrett Rose

Qing Wu

Yiran Chen

Richard W Linderman

Hai Li

Miao Hu

Robinson E Pino

Method and apparatus for performing close-loop programming of resistive memory devices in crossbar array based hardware circuits and systems. Invention provides iterative training of memristor crossbar arrays for neural networks by applying voltages corresponding to selected training patterns. Error is detected and measured as a function of the actual response to the training patterns versus the expected response to the training pattern.

Method and apparatus for performing close-loop programming of resistive memory devices in crossbar array based hardware circuits and systems

An apparatus that performs the mathematical matrix-vector multiplication approximation operations using crossbar arrays of resistive memory devices (e.g. memristor, resistive random-access memory, spintronics, etc.). A crossbar array formed by resistive memory devices serves as a memory array that stores the coefficients of a matrix. Combined with input and output analog circuits, the crossbar array system realizes the method of performing matrix-vector multiplication approximation operations with significant performance, area and energy advantages over existing methods and designs. This invention also includes an extended method that realizes the auto-associative neural network recall function using the resistive memory crossbar architecture.

Apparatus for performing matrix vector multiplication approximation using crossbar arrays of resistive memory devices

CMOS-memristor circuit is constructed to behave as a trainable artificial synapse for neuromorphic hardware systems. The invention relies on the memristance of a memristor at the input side of the device to act as a reconfigurable weight that is adjusted to realize a desired function. The invention relies on charge sharing at the output to enable the summation of signals from multiple synapses at the input node of a neuron circuit, implemented using a CMOS amplifier circuit. The combination of several memristive synapses and a neuron circuit constitute a neuromorphic circuit capable of learning and implementing a multitude of possible functionalities.

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Clinton, NY, United States of America

Garrett Rose