56 citations · 81 across the 16 of their papers we have counts for
7 papers · 1 filter
Approximate reservoir computing with a semiconductor laser for reducing energy consumption
Tatsuki Ito, Kazutaka Kanno, Satoshi Kawakami +1
Photonic reservoir computing is a promising physical machine-learning approach for time-series prediction. Quantization of the reservoir response signal is an important considerati…
Photonic decision making using optical frequency difference detection in mutually-coupled semiconductor lasers
Hidetoshi Taira, Takatomo Mihana, Shun Kotoku +4
As electronic computing approaches its performance limits, photonic accelerators have emerged as promising alternatives. Photonic accelerators exploiting semiconductor-laser synchr…
Experimental control of mode-competition dynamics in a chaotic multimode semiconductor laser for decision making
Ryugo Iwami, Takatomo Mihana, Kazutaka Kanno +2
Photonic computing has been widely used to accelerate the computational performance in machine learning. Photonic decision-making is a promising approach that uses photonic computi…
Chaotic mode-competition dynamics in a multimode semiconductor laser with optical feedback and injection
Ryugo Iwami, Kazutaka Kanno, Atsushi Uchida
Photonic computing is attracting increasing interest to accelerate information processing in machine learning applications. The mode-competition dynamics of multimode semiconductor…
Analysis of temporal structure of laser chaos by Allan variance
Naoki Asuke, Nicolas Chauvet, André Röhm +6
Allan variance has been widely utilized in evaluating the stability of the time series generated by atomic clocks and lasers, in time regimes ranging from short to extremely long.…
Controlling chaotic itinerancy in laser dynamics for reinforcement learning
Ryugo Iwami, Takatomo Mihana, Kazutaka Kanno +3
Photonic artificial intelligence has attracted considerable interest in accelerating machine learning; however, the unique optical properties have not been fully utilized for achie…
Using multidimensional speckle dynamics for high-speed, large-scale, parallel photonic computing
Satoshi Sunada, Kazutaka Kanno, Atsushi Uchida
The recent rapid increase in demand for data processing has resulted in the need for novel machine learning concepts and hardware. Physical reservoir computing and an extreme learn…