Neuromorphic computing aims at the realization of intelligent systems able to process
information similarly to our brain. Brain-inspired computing paradigms have been …

The reservoir computing (RC) system, known for its ability to seamlessly integrate memory
and computing functions, is considered as a promising solution to meet the high demands …

Abstract We overview Reservoir Computing (RC) with physical systems from an
Unconventional Computing (UC) perspective. We discuss challenges present in both fields …

The dynamic behavior of a nematic liquid crystal with added carbon nanotubes (CNTs) in an
electric field was analyzed. A theoretical model based on elastic continuum theory was …

The Reservoir Computing (RC) framework is said to have the potential to transfer onto any
input-driven dynamical system, provided two properties are present:(i) a fading memory, and …

Advances in artificial intelligence are driven by technologies inspired by the brain, but these
technologies are orders of magnitude less powerful and energy efficient than biological …

A theoretical model to explain the Freedericksz transition for a nematic liquid crystal with
graphene quantum dots adding in electric field below the instability area is proposed. A …

The dynamic behavior of a mixture of 4-cyano-4′-pentylbiphenyl (5CB) with 1% CoFe 2 O 4
nanoparticles was analyzed. Experimental data indicate a high stability of the nematic …

We report on the electrical behaviour of thin films of bovine brain microtubules (MTs). For
samples in both their dried and hydrated states, the measured currents reveal a power law …

Evolution-in-materio is a form of unconventional computing combining materials' training
and evolutionary search algorithms. In previous work, a mixture of single-walled-carbon …