Mess- und Sensortechnik in der digitalen Transformation. - In: 20. GMA/ITG-Fachtagung Sensoren und Messsysteme 2019, (2019), S. 30-32
https://doi.org/10.5162/sensoren2019/2.Plenarvortrag
Realitätsnahe Untersuchung der Temperaturverteilung von Schmelzzungen im Feuerfestmaterial von Induktionstiegelöfen auf der Basis numerischer Simulationen. - In: Workshop Elektroprozesstechnik, (2019), 14, insges. 11 S.
Influence of coolant temperature fluctuations to battery cell temperature. - In: Workshop Elektroprozesstechnik, (2019), 12, insges. 8 S.
Effects of thermal radiation and magnetic field on heat transfer and fluid flow in energy storage. - In: Workshop Elektroprozesstechnik, (2019), 11, insges. 6 S.
Flüssigmetall-Tropfenströmungen unter der Wirkung rotierender Magnetfelder. - In: Workshop Elektroprozesstechnik, (2019), 10, insges. 7 S.
Magnetische Separation von Teilchen aus Fluiden - Grundlagen, Ergebnisse und Vorrichtungsvorschläge. - In: Workshop Elektroprozesstechnik, (2019), 9, insges. 13 S.
Methoden zur Charakterisierung optischer Gitter über einen großen Ortsfrequenzbereich. - In: DGaO-Proceedings, ISSN 1614-8436, Bd. 120 (2019), A36, insges. 2 S.
https://nbn-resolving.org/urn:nbn:de:0287-2019-A036-4
Untersuchung deformierter optischer Mikrokavitäten anhand des abgestrahlten Fernfelds. - In: DGaO-Proceedings, ISSN 1614-8436, Bd. 120 (2019), B17, insges. 2 S.
https://nbn-resolving.org/urn:nbn:de:0287-2019-B017-3
The effect of ultraviolet irradiation on the electro-transport properties of carbon nanotubes : transport properties of ultraviolet irradiated carbon nanotubes. - In: Nanophotonics, nanooptics, nanobiotechnology, and their applications, (2019), S. 145-163
Behavioural model of memristors used as elements of neuromorphic systems. - In: AIP conference proceedings, ISSN 1551-7616, Bd. 2140 (2019), 020075, insges. 4 S.
The functional modelling of the biological brain is an urgent task in the framework of artificial intelligence and bioengineering. It is solved by means of neuromorphic systems that are built in the form of artificial neural networks, implemented as analog electronic circuits. Important elements of these circuits are memristors, embodying the synapses of biological neural networks. The behavioural model of memristors is represented as a polynomial of split signals. The polynomial model of Bernoulli memristors is built on assuming the excitation by a harmonic signal. The splitting of the input signal and the expedience of gaining the minimum number of split signals are demonstrated.
https://doi.org/10.1063/1.5122000