Results 31 to 40 of about 139,178 (278)
All-optical reservoir computing
Optics Express, 2012 Reservoir Computing is a novel computing paradigm which uses a nonlinear recurrent dynamical system to carry out information processing. Recent electronic and optoelectronic Reservoir Computers based on an architecture with a single nonlinear node and a delay loop have shown performance on standardized tasks comparable to state-of-the-art digital ...
Duport, Francois +4 more
openaire +3 more sources
Audio Classification with Skyrmion Reservoirs
Advanced Intelligent Systems, 2023 Physical reservoir computing is a computational paradigm that enables spatiotemporal pattern recognition to be performed directly in matter. The use of physical matter leads the way toward energy‐efficient devices capable of solving machine learning ...
Robin Msiska +4 more
doaj +1 more source
Time series reconstructing using calibrated reservoir computing
Scientific Reports, 2022 Reservoir computing, a new method of machine learning, has recently been used to predict the state evolution of various chaotic dynamic systems. It has significant advantages in terms of training cost and adjusted parameters; however, the prediction ...
Yeyuge Chen, Yu Qian, Xiaohua Cui
doaj +1 more source
Photonic Delay Systems as Machine Learning Implementations [PDF]
, 2015 Nonlinear photonic delay systems present interesting implementation platforms for machine learning models. They can be extremely fast, offer great degrees of parallelism and potentially consume far less power than digital processors.
Bienstman, Peter +4 more
core +2 more sources
Reservoir computing with solitons
New Journal of Physics, 2021 Reservoir computing is a promising framework that facilitates the approach to physical neuromorphic hardware by enabling a given nonlinear physical system to act as a computing platform.
Nuno Azevedo Silva +2 more
doaj +1 more source
Rotating neurons for all-analog implementation of cyclic reservoir computing
Nature Communications, 2022 Reservoir computing has demonstrated high-level performance, however efficient hardware implementations demand an architecture with minimum system complexity. The authors propose a rotating neuron-based architecture for physically implementing all-analog
Xiangpeng Liang +10 more
doaj +1 more source
Nano-scale reservoir computing
, 2013 This work describes preliminary steps towards nano-scale reservoir computing using quantum dots. Our research has focused on the development of an accumulator-based sensing system that reacts to changes in the environment, as well as the development of a
Chadwick, Matthew +10 more
core +1 more source
Catch-22s of reservoir computing
Physical Review Research, 2023 Reservoir computing (RC) is a simple and efficient model-free framework for forecasting the behavior of nonlinear dynamical systems from data. Here, we show that there exist commonly-studied systems for which leading RC frameworks struggle to learn the ...
Yuanzhao Zhang, Sean P. Cornelius
doaj +1 more source
Hierarchical Composition of Memristive Networks for Real-Time Computing [PDF]
, 2015 Advances in materials science have led to physical instantiations of self-assembled networks of memristive devices and demonstrations of their computational capability through reservoir computing.
Bürger, Jens +3 more
core +3 more sources
Modelling Reservoir Computing with the Discrete Nonlinear Schr\"odinger Equation
, 2018 We formulate, using the discrete nonlinear Schroedinger equation (DNLS), a general approach to encode and process information based on reservoir computing. Reservoir computing is a promising avenue for realizing neuromorphic computing devices.
Boman, Magnus +2 more
core +1 more source