Noise signal as input data in self-organized neural networks

Autor: V. Kagalovsky, D. Nemirovsky, S. V. Kravchenko
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Low Temperature Physics
Popis: Self-organizing neural networks are used to analyze uncorrelated white noises of different distribution types (normal, triangular, and uniform). The artificially generated noises are analyzed by clustering the measured time signal sequence samples without its preprocessing. Using this approach, we analyze, for the first time, the current noise produced by a sliding "Wigner-crystal "-like structure in the insulating phase of a 2D electron system in silicon. The possibilities of using the method for analyzing and comparing experimental data obtained by observing various effects in solid-state physics and numerical data simulated using theoretical models are discussed. Published under an exclusive license by AIP Publishing.
Databáze: OpenAIRE