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Reservoir computing with the frequency, phase and amplitude of spin-torque nano-oscillators
Danijela Marković, Nathan Leroux, Mathieu Riou +8
Spin-torque nano-oscillators can emulate neurons at the nanoscale. Recent works show that the non-linearity of their oscillation amplitude can be leveraged to achieve waveform clas…
Chaos and relaxation oscillations in spin-torque windmill neurons
Rie Matsumoto, Steven Lequeux, Hiroshi Imamura +1
Spintronic neurons which emit sharp voltage spikes are required for the realization of hardware neural networks enabling fast data processing with low-power consumption. In many ne…
Nano-oscillator-based classification with a machine learning-compatible architecture
Damir Vodenicarevic, Nicolas Locatelli, Julie Grollier +1
Pattern classification architectures leveraging the physics of coupled nano-oscillators have been demonstrated as promising alternative computing approaches, but lack effective lea…
Circuit-Level Evaluation of the Generation of Truly Random Bits with Superparamagnetic Tunnel Junctions
Damir Vodenicarevic, Nicolas Locatelli, Alice Mizrahi +4
Many emerging alternative models of computation require massive numbers of random bits, but their generation at low energy is currently a challenge. The superparamagnetic tunnel ju…
Overcoming device unreliability with continuous learning in a population coding based computing system
Alice Mizrahi, Julie Grollier, Damien Querlioz +1
The brain, which uses redundancy and continuous learning to overcome the unreliability of its components, provides a promising path to building computing systems that are robust to…