Novel hardware and concepts for unconventional computing
The potential of machine learning can only be fully exploited if more efficient hardware is developed that meets the special needs of bio-inspired computing schemes. In this respect, non-volatile memory technology using memristive devices in combination with neuromorphic systems is a promising way to such hardware. This Collection provides a platform for interdisciplinary research on unconventional computing with new physical substrates.
Editors
-
Martin Ziegler
TU Ilmenau, Germany
All articles have undergone Scientific Reports' standard peer review process and have been subject to all of the journal’s standard policies. This includes the journal’s policy on competing interests. The Guest Editor declares no competing interests with the submissions which they have handled through the peer review process. The peer review of any submissions for which the Guest Editor has competing interests is handled by another Editorial Board Member who has no competing interests.
This Collection has not been supported by sponsorship.
