Titlebook: Reservoir Computing; Theory, Physical Imp Kohei Nakajima,Ingo Fischer Book 2021 Springer Nature Singapore Pte Ltd. 2021 Reservoir Computing

手榴弹

Banister

MIME

Physical Reservoir Computing in Roboticsot’s body and its dynamics as a computational resource. On one hand, this has been driven by the introduction of mathematical frameworks showing how complex mechanical structures can be used to build reservoirs. On the other hand, with the recent advances in smart materials, novel additive manufactu

骗子

Reservoir Computing in MEMSpplications. General properties of MEMS are discussed, and the Duffing microscale beam characteristics are analyzed through analytical models and simulations. The reservoir computer is then constructed around a single such nonlinear oscillator through temporal multiplexing of the input and self-coup

大厅

Neuromorphic Electronic Systems for Reservoir Computing electronic systems. Due to its computational efficiency and the fact that training amounts to a simple linear regression, both spiking and non-spiking implementations of reservoir computing on neuromorphic hardware have been developed. Here, a review of these experimental studies is provided to ill

先驱

Reservoir Computing Using Autonomous Boolean Networks Realized on Field-Programmable Gate Arrays can be quickly reconfigured. The reservoir computer displays analog-like behavior and has the potential to perform computations beyond that of a classic Turning machine. In detail, we present our preliminary results of using a physical reservoir computer for performing the task of identifying writt

Intractable

Programmable Fading Memory in Atomic Switch Systems for Error Checking Applicationse-of-the-art memristive devices provides optimal scaling of current technologies beyond this limit through the adoption of neuromorphic models. Universal computing machines pioneered by Alan Turing are strictly based on top-down intelligent design. Neuromorphic models instead engage in bottom-up pro

opportune

Reservoir Computing Leveraging the Transient Non-linear Dynamics of Spin-Torque Nano-Oscillatorss near their limits, which leads to high energy costs. A possible solution to this problem is the development of new computing architectures, with nanoscale hardware components that use their physical properties to emulate the behavior of neurons. In spite of multiple theoretical proposals, there ha

欢呼

moribund