<p>Jülich researchers have introduced novel memristive components in Nature Communications, offering significant advantages over previous versions. These memristors are more robust, operate within a wider voltage range, and can be used in both analog and digital modes. They could address the issue of 'catastrophic forgetting' in artificial neural networks, where learned information is abruptly lost.</p><p>The researchers have implemented the new memristive element in a model of artificial neural networks, achieving high accuracy in pattern recognition. They plan to seek further materials for memristors that may perform even better than the current version.</p>
Related Articles
- Unconventional Approach Yields Unprecedented Palladium Hydride Nanoparticles6 months ago
- HM25: Smart Systems in Their Future Applications - Reliable, Trustworthy, and Secure3 months ago
- Molekül-Ringe Herr: An Innovative Shortcut to High-Performance Organic Materials3 months ago
- ATLANT 3D Secures $15 M Series A+ as Demand Grows for its Atomic Layer Processing Technology3 months ago
- Large-Scale Fuel Cell Project: Production Technologies for Mass Production3 months ago
- Observing Electron Motion in Solids3 months ago
- JFrog: A Tech Stock Leaps And Bounds Above Others3 months ago
- Exploration of Hidden Atomic Movements Through Machine Learning3 months ago
- Empa's New 'CarboQuant' Lab Peers into Carbon's (Quantum-) World3 months ago
- Fundamental Research for the Hydrogen Economy3 months ago