Results 1 to 10 of about 1,932,721 (285)
AI, 2022 Noise of any kind can be an issue when translating results from simulations to the real world. We suddenly have to deal with building tolerances, faulty sensors, or just noisy sensor readings.
Christoph Walter Senn, Itsuo Kumazawa
doaj +2 more sources
Implementation of reservoir computing using coupled microelectromechanical drum resonators via sideband-pumped phonon–cavity dynamics [PDF]
Microsystems & NanoengineeringReservoir computing is a bio-inspired machine learning paradigm that exploits the intrinsic dynamics of nonlinear systems with fading memory for efficient temporal information processing.
Theresa Farah +8 more
doaj +2 more sources
Memristive Physical Reservoir Computing [PDF]
Advanced ScienceReservoir computing (RC) has emerged as an efficient neuromorphic framework for temporal information processing, offering low training complexity and hardware‐friendly implementation. Memristors’ nonlinear dynamics and input‐dependent memory effects make
Dian Jiao +9 more
doaj +2 more sources
Harvested reservoir computing from road traffic dynamics [PDF]
Scientific ReportsReservoir computing (RC) has gained attention as an efficient machine learning method for time series prediction because of its low computational costs and simple learning process.
Ryunosuke Fukuzaki +2 more
doaj +2 more sources
Gate insulator stack engineering for fully CMOS-compatible reservoir computing [PDF]
Nano ConvergenceThe need for processing complex and temporal datasets has increased with the rise of artificial intelligence. In this context, reservoir computing, which utilizes the short-term memory of the reservoir to map input data into a high-dimensional space, has
Joon Hwang +4 more
doaj +2 more sources
Parallel reservoir computing exploiting a single MEMS device via blue sideband excitation [PDF]
Microsystems & NanoengineeringPhysical reservoir computing (PRC) offers a promising pathway for energy-efficient edge intelligence; however, existing micro-electromechanical systems (MEMS) implementations struggle to balance computational dimensionality with hardware complexity. Here,
Yueyang Li +16 more
doaj +2 more sources
Parallel and deep reservoir computing using semiconductor lasers with optical feedback
Nanophotonics, 2022 Photonic reservoir computing has been intensively investigated to solve machine learning tasks effectively. A simple learning procedure of output weights is used for reservoir computing.
Hasegawa Hiroshi +2 more
doaj +1 more source
Reservoir concatenation and the spectrum distribution of concatenated reservoir state matrices
AIP Advances, 2023 Reservoir computing, one of the state-of-the-art machine learning architectures, processes time-series data generated by dynamical systems. Nevertheless, we have realized that reservoir computing with the conventional single-reservoir structure suffers ...
Jaesung Choi +3 more
doaj +1 more source
Scientific Reports, 2023 Reservoir computing is a brain heuristic computing paradigm that can complete training at a high speed. The learning performance of a reservoir computing system relies on its nonlinearity and short-term memory ability.
Zhiqiang Liao +5 more
doaj +1 more source
Quantum reservoir computing with a single nonlinear oscillator
Physical Review Research, 2021 Realizing the promise of quantum information processing remains a daunting task given the omnipresence of noise and error. Adapting noise-resilient classical computing modalities to quantum mechanics may be a viable path towards near-term applications in
L. C. G. Govia +4 more
doaj +1 more source