Correlated electron switch elements for brain-based computing
AssigneeCerfe Labs, Inc.
InventorsLucian Shifren, Shidhartha Das, Naveen Suda, Carlos Alberto Paz de Araujo
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Abstract
Broadly speaking, the present techniques exploit the properties of correlated electron materials for artificial neural networks and neuromorphic computing. In particular, the present techniques provide apparatuses/devices that comprise at least one correlated electron switch (CES) element and which may be used as, or to form, an artificial neuron or an artificial synapse.
Claims21
An apparatus for an artificial neural network, the apparatus comprising:
- at least one correlated electron switch (CES) element to be configurable to:
- store one or more synaptic weights;
- operate in a high impedance state;
- operate in one or more low impedance states;
- establish a threshold current responsive to transition of the at least one CES element to one of the one or more low impedance states;
- transition to the high impedance state responsive to a current in the at least one CES element meeting or exceeding the threshold current;
- and
- accumulate currents inputted to the apparatus as an accumulated current and output a signal responsive to the accumulated current equaling or exceeding the established threshold current.
A configurable array for an artificial neural network, the configurable array comprising:
- a plurality of apparatuses, each apparatus comprising one or more correlated electron switch (CES) elements, individual CES elements to be capable of functioning as either a synapse or as a neuron;
- and
- a switching mechanism to selectively configure at least one of the one or more CES elements to function as the synapse or the neuron.
An apparatus for an artificial neural network, the apparatus comprising one or more correlated electron switch (CES) elements, wherein
- at least a first CES element is adapted to:
- establish a threshold current responsive to the first CES element transitioning to low impedance state;
- and
- provide an output signal responsive to a transition of the first CES element to a high impedance state, wherein:
- the transition of the first CES element is to occur responsive to a current in the first CES element equaling or exceeding the threshold current;
- and
- the output signal is based, at least in part, on one or more stored synaptic weights.
An apparatus for an artificial neural network, the apparatus comprising a crosspoint array of a plurality of neurons, a first neuron of the plurality of neurons to comprise at least one correlated electron switch (CES) element, wherein the first neuron is adapted to:
- establish a threshold current responsive to a transition of the at least one CES element to a low impedance state of one or more low impedance states;
- transition to a high impedance state responsive to a current in the at least one CES element equaling or exceeding the threshold current;
- and
- accumulate currents input to the first neuron as an accumulated current and output a signal responsive to the accumulated current equaling or exceeding the threshold current.
Dependencies are inferred from the claim text.