Double MgO-Based Perpendicular Magnetic Tunnel Junction for Artificial Neuron
Dong‐Won Kim, Woo Seok Yi, Jin Choi, Kei Ashiba, Jong Ung Baek, Han‐Sol Jun, Jae Joon Kim, Jea Gun Park
Abstract
A perpendicular-spin-transfer-torque (p-STT) based neuron was developed for a spiking neural network (SNN). It demonstrated the integrate behavior of a typical neuron in a SNN; in particular, the integrate behavior corresponding to magnetic resistance change gradually increased with the input spike number. This behavior occurred when the spin electron directions between double Co2Fe6B2 free and pinned layers in the p-STT based neuron were switched from parallel to anti-parallel states. Also, a neuron circuit for integrate-and-fire operation was proposed. Finally, pattern-recognition simulation was performed for a single layer SNN.
Topics & Concepts
Antiparallel (mathematics)NeuronSpiking neural networkPerpendicularTunnel magnetoresistanceMaterials scienceCondensed matter physicsComputer scienceArtificial neural networkPhysicsNeuroscienceArtificial intelligenceFerromagnetismMagnetic fieldMathematicsGeometryPsychologyQuantum mechanicsAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesNeural Networks and Reservoir Computing