Reservoir computing is a recent bio-inspired approach for processing time-dependent signals. It has enabled a breakthrough in analog information processing, with several experiments, both electronic and optical, demonstrating state-of-the-art performance for hard tasks such as speech recognition, time series prediction, and nonlinear channel equalization. A proof-of-principle experiment using a linear optical circuit on a photonic chip to process digital signals was recently reported. Here we present a photonic implementation of a reservoir computer based on a coherently driven passive fiber cavity processing analog signals. Our experiment has error rate as low as or lower than previous experiments on a wide variety of tasks, and also has l...
In this thesis we study photonic computation within the framework of reservoir computing. Inspired b...
We propose photonic reservoir computing as a new approach to optical signal processing and it can be...
Nonlinearity mitigation in optical fiber networks is typically handled by electronic Digital Signal ...
We study numerically a realistic model of an original autonomous implementation of a photonic neural...
We present the first experimental implementation of a passive linear reservoir computer working in c...
For many challenging problems where the mathematical description is not explicitly defined, artifici...
In today's age, companies employ machine learning to extract information from large quantities of da...
Despite ever increasing computational power, recognition and classification problems remain challeng...
Photonic reservoir computing is a hardware implementation of the concept of reservoir computing whic...
Reservoir Computing [1] is a new approach to study and use Neural Networks, which try to mimic a bra...
International audienceWe review a novel paradigm that has emerged in analogue neuromorphic optical c...
Reservoir computing is a brain-inspired approach for information processing, well suited to analog i...
Photonic reservoir computing is a recent bio-inspired paradigm for signal processing. Despite first ...
We present our latest results on silicon photonics neuromorphic information processing based a.o. on...
We present an autonomous all-photonic experimental implementation of an artificial neural network ba...
In this thesis we study photonic computation within the framework of reservoir computing. Inspired b...
We propose photonic reservoir computing as a new approach to optical signal processing and it can be...
Nonlinearity mitigation in optical fiber networks is typically handled by electronic Digital Signal ...
We study numerically a realistic model of an original autonomous implementation of a photonic neural...
We present the first experimental implementation of a passive linear reservoir computer working in c...
For many challenging problems where the mathematical description is not explicitly defined, artifici...
In today's age, companies employ machine learning to extract information from large quantities of da...
Despite ever increasing computational power, recognition and classification problems remain challeng...
Photonic reservoir computing is a hardware implementation of the concept of reservoir computing whic...
Reservoir Computing [1] is a new approach to study and use Neural Networks, which try to mimic a bra...
International audienceWe review a novel paradigm that has emerged in analogue neuromorphic optical c...
Reservoir computing is a brain-inspired approach for information processing, well suited to analog i...
Photonic reservoir computing is a recent bio-inspired paradigm for signal processing. Despite first ...
We present our latest results on silicon photonics neuromorphic information processing based a.o. on...
We present an autonomous all-photonic experimental implementation of an artificial neural network ba...
In this thesis we study photonic computation within the framework of reservoir computing. Inspired b...
We propose photonic reservoir computing as a new approach to optical signal processing and it can be...
Nonlinearity mitigation in optical fiber networks is typically handled by electronic Digital Signal ...