Experimental Demonstration of Neuromorphic Network with STT MTJ Synapses
This work addresses the need for more stable and precise hardware for neuromorphic computing, though it is incremental as it builds on existing memristor-based approaches.
The authors tackled the problem of implementing neuromorphic networks using magnetic tunnel junction (MTJ) synapses, achieving the first experimental demonstration of such a network for image recognition via vector-matrix multiplication and simulating it on MNIST with accuracy matching memristors while offering improved precision, stability, and endurance.
We present the first experimental demonstration of a neuromorphic network with magnetic tunnel junction (MTJ) synapses, which performs image recognition via vector-matrix multiplication. We also simulate a large MTJ network performing MNIST handwritten digit recognition, demonstrating that MTJ crossbars can match memristor accuracy while providing increased precision, stability, and endurance.