Time: Wednesday, October 10th, 10:10
Speaker: Damien QUERLIOZ, Integnano – C2N
The brain displays many features typical of non-linear dynamical networks, such as synchronization or chaotic behavior. 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 explain why coupled magnetic nano-oscillators are very promising for realizing cognitive computing at the nanometer and nanosecond scale. Then, I will present our experimental and theoretical results. In particular, I will show how we can perform speech recognition using the transient dynamics and the synchronization of a few oscillators. I will also show how this line of research can take inspiration from both neuroscience and the field of machine learning. I will finish by the open questions raised by our research.