Unconventional Computing With Memristive Nanocircuits
| Autor: | Evangelos Tsipas, Theodoros Panagiotis Chatzinikolaou, Karolos-Alexandros Tsakalos, Konstantinos Rallis, Rafailia-Eleni Karamani, Iosif-Angelos Fyrigos, Stavros Kitsios, Panagiotis Bousoulas, Dimitrios Tsoukalas, Georgios Ch. Sirakoulis |
|---|---|
| Přispěvatelé: | Universitat Politècnica de Catalunya. Doctorat en Enginyeria Electrònica |
| Rok vydání: | 2022 |
| Předmět: |
Mechanical Engineering
Enginyeria electrònica [Àrees temàtiques de la UPC] Quantum computing Electric apparatus and appliances Learning automata Aparells elèctrics Nanoscale devices NP-complete problem Resistències elèctriques Performance evaluation Bio-inspired computing Electrical and Electronic Engineering Memristors Unconventional computing Neuromorphics |
| Zdroj: | IEEE Nanotechnology Magazine. 16:22-33 |
| ISSN: | 1942-7808 1932-4510 |
| Popis: | Computing demands are growing rapidly as bigdata and artificial intelligence applications become increasingly tasking. Bio-inspired and quantum-based techniques are proving to be quite promising for the development of novel circuits and systems. These systems can contribute to the resolution of a wider variety of problems while also providing improvements to existing techniques. As the von Neumann architecture’s expected performance, which has been dominant for the past several decades, is now hindered by physical limitations, novel computing architectures, assisted by novel materials and circuit devices, are starting to emerge and provide promising results. The topic of this work is to examine the memory and computing capabilities of emergent memristor-based nanocircuits and demonstrate their advantages compared to their classical counterparts. |
| Databáze: | OpenAIRE |
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