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Electrically-Tunable Stochasticity for Spin-based Neuromorphic Circuits: Self-Adjusting to Variation
Energy-efficient methods are addressed for leveraging low energy barrier nanomagnetic devices within neuromorphic architectures.
Modular Simulation Framework for Process Variation Analysis of MRAM-based Deep Belief Networks
Magnetic Random-Access Memory (MRAM) based p-bit neuromorphic computing devices are garnering increasing interest as a means to compactly and efficiently realize machine learning operations in Restricted Boltzmann Machines (RBMs).
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