The brain displays many features typical of non-linear dynamical networks, such as synchronization or chaotic behaviour. These observations have inspired a whole class of models that harness the power of complex non-linear dynamical networks for computing. In this framework, neurons are modeled as non-linear oscillators, and synapses as the coupling between oscillators. These abstract models are very good at processing waveforms for pattern recognition or at generating precise time sequences useful for robotic motion. However there are very few hardware implementations of these systems, because large numbers of interacting non-linear oscillators are indeed. In this talk, I will show that coupled spin-torque nano-oscillators are very promising for realizing cognitive computing at the nanometer and nanosecond scale, and will present our first results in this direction.
Julie Grollier, Jacob Torrejon, Mathieu Riou, Vincent Cros, Damien Querlioz, Sumito Tsunegi, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Mark D. Stiles, and Guru Khalsa, "Superparamagnetic tunnel junctions for bio-inspired computing
(Conference Presentation)," Proc. SPIE 9931, Spintronics IX, 99310N (Presented at SPIE Nanoscience + Engineering: August 28, 2016; Published: 4 November 2016); https://doi.org/10.1117/12.2236990.5167075267001.
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Study of self-shadowing effect as a simple means to realize nanostructured thin films and layers with special attentions to birefringent obliquely deposited thin films and photo-luminescent porous silicon