Noise signal as input data in self-organized neural networks-Reference-Cited by-同舟云学术

Noise signal as input data in self-organized neural networks

Published:2022-06 Issue:6 Volume:48 Page:452-458
ISSN:1063-777X
Container-title:Low Temperature Physics
language:en
Short-container-title:Low Temperature Physics

Author:

Kagalovsky V.¹²^ORCID,Nemirovsky D.¹^ORCID,Kravchenko S. V.³^ORCID

Affiliation:

1. Shamoon College of Engineering, Beer-Sheva 84105, Israel

2. Max-Planck-Institutfur Physik komplexer Systeme, Dresden 01187, Germany

3. Physics Department, Northeastern University, Boston, Massachusetts 02115, USA

Abstract

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.

Publisher

AIP Publishing

Subject

General Physics and Astronomy,Physics and Astronomy (miscellaneous)

Link

https://aip.scitation.org/doi/pdf/10.1063/10.0010439

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