no code implementations • 29 Nov 2022 • Joseph D. Hart, Francesco Sorrentino, Thomas L. Carroll
Reservoir computing, a recurrent neural network paradigm in which only the output layer is trained, has demonstrated remarkable performance on tasks such as prediction and control of nonlinear systems.
no code implementations • 9 Sep 2022 • Thomas L. Carroll
While there have been many publications on potential applications of chaos to fields such as communications, radar, sonar, random signal generation, channel equalization and others, designing continuous chaotic systems is still an unsolved problem.
no code implementations • 3 May 2022 • Thomas L. Carroll, Joseph D. Hart
Additionally, the need to create and connect large numbers of nonlinear nodes makes it difficult to design and build analog reservoir computers that can be faster and consume less power than digital reservoir computers.
no code implementations • 5 Jan 2022 • Thomas L. Carroll
A reservoir computer is a way of using a high dimensional dynamical system for computation.
no code implementations • 2 Dec 2020 • Thomas L. Carroll
It has been demonstrated that cellular automata had the highest computational capacity at the edge of chaos, the parameter at which their behavior transitioned from ordered to chaotic.
no code implementations • 24 Aug 2020 • Thomas L. Carroll
Reservoir computers are a type of neuromorphic computer that may be built a an analog system, potentially creating powerful computers that are small, light and consume little power.
no code implementations • 10 Dec 2019 • Thomas L. Carroll
A reservoir computer is a complex dynamical system, often created by coupling nonlinear nodes in a network.
no code implementations • 6 Jun 2019 • Thomas L. Carroll
A reservoir computer is a dynamical system that may be used to perform computations.