Photonic reservoir computing uses recent advances in machine learning, and in particular the reservoir computing algorithm, to carry out complex computations optically. Experimental demonstrations with performance comparable to state of the art digital implementations have been reported. However, most experiments so far were based on sequential processing using time-multiplexing. Parallel architectures promise considerable speedup. Recently, a reservoir computing architecture based on frequency parallelism was proposed by our laboratory, and a preliminary demonstration was carried out using optical fibres. In this system the reservoir is linear and the nonlinearity is provided by readout photodiodes. Here, we study in simulation an implemen...
Abstract Photonic implementations of reservoir computing (RC) promise to reach ultra-high bandwidth ...
The recent progress in artificial intelligence has spurred renewed interest in hardware implementati...
Reservoir Computing [1] is a new approach to study and use Neural Networks, which try to mimic a bra...
Photonic reservoir computing uses recent advances in machine learning, and in particular the reservo...
Reservoir computing is a brain-inspired approach for information processing, well suited to analog i...
Reservoir computing (RC), a computational paradigm inspired on neural systems, has become increasing...
Despite ever increasing computational power, recognition and classification problems remain challeng...
Reservoir computing is a recent bio-inspired approach for processing time-dependent signals. It has ...
We propose photonic reservoir computing as a new approach to optical signal processing and it can be...
We present a coherent wavelength division multiplexed reservoir computer based on intra-cavity phase...
Nonlinearity mitigation in optical fiber networks is typically handled by electronic Digital Signal ...
International audiencePhotonic implementations of novel information processing schemes based on mach...
Photonic reservoir computing is a hardware implementation of the concept of reservoir computing whic...
Photonic reservoir computing has evolved into a viable contender for the next generation of analog c...
Machine Learning (ML) approaches like Deep Neural Networks (DNNs) have emerged as a powerful tool fo...
Abstract Photonic implementations of reservoir computing (RC) promise to reach ultra-high bandwidth ...
The recent progress in artificial intelligence has spurred renewed interest in hardware implementati...
Reservoir Computing [1] is a new approach to study and use Neural Networks, which try to mimic a bra...
Photonic reservoir computing uses recent advances in machine learning, and in particular the reservo...
Reservoir computing is a brain-inspired approach for information processing, well suited to analog i...
Reservoir computing (RC), a computational paradigm inspired on neural systems, has become increasing...
Despite ever increasing computational power, recognition and classification problems remain challeng...
Reservoir computing is a recent bio-inspired approach for processing time-dependent signals. It has ...
We propose photonic reservoir computing as a new approach to optical signal processing and it can be...
We present a coherent wavelength division multiplexed reservoir computer based on intra-cavity phase...
Nonlinearity mitigation in optical fiber networks is typically handled by electronic Digital Signal ...
International audiencePhotonic implementations of novel information processing schemes based on mach...
Photonic reservoir computing is a hardware implementation of the concept of reservoir computing whic...
Photonic reservoir computing has evolved into a viable contender for the next generation of analog c...
Machine Learning (ML) approaches like Deep Neural Networks (DNNs) have emerged as a powerful tool fo...
Abstract Photonic implementations of reservoir computing (RC) promise to reach ultra-high bandwidth ...
The recent progress in artificial intelligence has spurred renewed interest in hardware implementati...
Reservoir Computing [1] is a new approach to study and use Neural Networks, which try to mimic a bra...