TRIPHOP TOWARDS BRAIN-INSPIRED EFFICIENT PHOTONIC INFORMATION PROCESSING
Information processing is a major challenge in our information-driven society, and the demand will grow further in the future. Large amounts of data need to be processed in communication networks, but also in other fields like in medicine, environmental or economic systems. Novel unconventional computation approaches are required, and photonics provides attractive possibilities. The aim of this project is to develop and explore a photonic information processing scheme, capable of efficiently performing classification, pattern recognition and prediction tasks. We target to achieve high computational performance with a small number of components by using semiconductor lasers with delayed coupling. Our approach will allow for high speed (GHz) processing, low power consumption and minimal hardware requirements.
Investigadors
Ingo Fischer
Publicacions recents
Photonic Information Processing
Bueno Moragues, Julián (Supervisors: Fischer, Ingo; Brunner, Daniel)PhD Thesis (2019)
Semiconductor laser linewidth reduction by six orders of magnitude via delayed optical feedback
Brunner, Daniel; Luna, Raimon; Delhom I Latorre, Adrian; Porte, Xavier; Fischer, IngoOptics Letters 42, 163 - 166 (2017)
Consistency in experiments on multistable driven delay systems
Oliver, Neus; Larger, Laurent; Fischer, IngoChaos 26, 103115 (1-7) (2016)
Photonic Reservoir Computing for Ultra-Fast Information Processing Using Semiconductor Lasers
Fischer, Ingo; Bueno, Julian; Brunner, Daniel; Soriano, Miguel C.; Mirasso, ClaudioProceedings of ECOC 2016 (42nd European Conference and Exhibition on Optical Communications), VDE VERLAG GMBH (Berlin, Offenbach), , 336-338 (2016)
CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT
Vukobratovic, Dejan; Jakovetic, Dusan; Skachek, Vitaly; Bajovic, Dragana; Sejdinovic, Dino; Karabulut Kurt, Gunes; Hollanti, Camilla; Fischer, IngoIEEE Access 4, 3360-3378 (2016)