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.
Scientific Reports, a journal from the Nature Research family, is proud to welcome original primary research articles for our upcoming “Novel hardware and concepts for unconventional computing” Collection.
The aim of this Collection is to provide a platform for interdisciplinary research on unconventional computing with new physical substrates. It will include studies in areas such as biological modelling, materials physics and analytics, memristive devices, neuromorphic circuits and other novel computing and circuit schemes.
Submissions for this Collection will be open through the end of September 2019. More information about this Collection and how to submit a manuscript can be found here.
This Collection is Guest Edited by Prof Martin Ziegler, a Professor and head of the Department of Microelectronic and Nanoelectronic Systems at TU Ilmenau, Germany. His research interests include the development of memristive devices and their integration in neuromorphic circuits, as well as electronic transport measurements, thin film analysis techniques, and the development of neural computational models. Martin Ziegler has been an Editorial Board Member for Scientific Reports since 2017.