Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Mirko Hansen"'
Publikováno v:
AIMS Materials Science, Vol 2, Iss 3, Pp 203-216 (2015)
We report on the development of TiOx-based memristive devices for bio-inspired neuromorphic systems. In particular, capacitor like structures of Al/AlOx/TiOx/Al with, respectively 20 nm and 50 nm thick TiOx-layers were fabricated and analyzed in term
Externí odkaz:
https://doaj.org/article/9e7dad430663490597040e1c5a22c4d1
Autor:
Margit Zacharias, Falk von Seggern, Christian Kübel, Sebastian Gutsch, V.S. Kiran Chakravadhanula, Torsten Scherer, Xiaoke Mu, Alan Molinari, Mirko Hansen, Krishna Kanth Neelisetty, Lorenz Kienle, Alexander Vahl
Publikováno v:
Microscopy and Microanalysis. 25:592-600
In situ transmission electron microscope (TEM) characterization techniques provide valuable information on structure–property correlations to understand the behavior of materials at the nanoscale. However, understanding nanoscale structures and the
Autor:
Mahal Singh Gill, Martin Ziegler, Hermann Kohlstedt, Karlheinz Ochs, Eloy Hernandez-Guevara, Mirko Hansen, Marina Ignatov, Enver Solan
Publikováno v:
International Journal of Circuit Theory and Applications. 46:235-243
Summary A memristive device is a novel passive device, which is essentially a resistor with memory. This device can be used for novel technical applications like neuromorphic computation. In this paper, we focus on anticipation—a capability of a sy
Publikováno v:
Scientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
Conventional transistor electronics are reaching their limits in terms of scalability, power dissipation, and the underlying Boolean system architecture. To overcome this obstacle neuromorphic analogue systems are recently highly investigated. Partic
Autor:
Pablo Mendoza Ponce, Lait Abu Saleh, Dietmar Schroeder, Rajeev Ranjan, Mirko Hansen, Hermann Kohlstedt, Martin Ziegler, Wolfgang H. Krautschneider
Publikováno v:
ISCAS
This paper details the design of an integrate & fire (I & F) neuron ASIC and its integration with a double barrier memristor device. The memristor has a non-volatile analog memory characteristic which changes with time and voltage. The neuron ASIC is
Publikováno v:
IEEE Transactions on Biomedical Circuits and Systems. 9:197-206
In this work we present a phenomenological model for synaptic plasticity suitable to describe common plasticity measurements of memristive devices. We show evidence that the presented model is basically compatible with advanced biophysical plasticity
Publikováno v:
AIMS Materials Science. 2:203-216
We report on the development of TiOx-based memristive devices for bio-inspired neuromorphic systems. In particular, capacitor like structures of Al/AlOx/TiOx/Al with, respectively 20 nm and 50 nm thick TiOx-layers were fabricated and analyzed in term
Publikováno v:
Science Advances
Memristive devices help address the binding problem: Their memory supports a transient connectivity in oscillator networks.
The human brain is able to integrate a myriad of information in an enormous and massively parallel network of neurons tha
The human brain is able to integrate a myriad of information in an enormous and massively parallel network of neurons tha
Publikováno v:
Frontiers in Neuroscience
The use of interface-based resistive switching devices for neuromorphic computing is investigated. In a combined experimental and numerical study, the important device parameters and their impact on a neuromorphic pattern recognition system are studi
Autor:
Krishna Kanth Neelisetty, Georg Haberfehlner, Julian Strobel, Martin Ziegler, Venkata Sai Kiran Chakravadhanula, Gerald Kothleitner, Sven Dirkmann, Christian Kübel, Lorenz Kienle, Hermann Kohlstedt, Radian Popescu, Mirko Hansen, Thomas Mussenbrock
Memristors based on a double barrier design have been analysed by various nano spectroscopic methods to unveil details about its microstructure and conduction mechanism. The device consists of an AlOx tunnel barrier and a NbOy/Au Schottky barrier san
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::60b514ddfbb548edfc6be3db0cf83115