Noise signal as input data in self-organized neural networks

被引：0
|
作者：
Kagalovsky, V. [1 ,2 ]
Nemirovsky, D. [1 ]
Kravchenko, S. V. [3 ]
机构：
[1] Shamoon Coll Engn, IL-84105 Beer sheva, Israel
[2] Max Planck Inst Phys komplexer Syst, D-01187 Dresden, Germany
[3] Northeastern Univ, Phys Dept, Boston, MA 02115 USA
来源：
LOW TEMPERATURE PHYSICS | 2022年 / 48卷 / 06期
基金：
美国国家科学基金会;
关键词：
self-organizing neural networks; current noise; Wigner crystal; 2D electron systems; CURRENT-VOLTAGE CHARACTERISTICS;
D O I：
10.1063/10.0010439
中图分类号：
O59 [应用物理学];
学科分类号：
摘要：
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.
引用
收藏
页码：452 / 458
页数：7
相关论文
共 50 条
  • [1] Neural networks grown and self-organized by noise
    Raghavan, Guruprasad
    Thomson, Matt
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), 2019, 32
  • [2] Self-organized criticality in structured neural networks
    Maximilian Uhlig
    Anna Levina
    Theo Geisel
    Michael J Herrmann
    BMC Neuroscience, 14 (Suppl 1)
  • [3] Neural networks with self-organized basis functions
    Li, CK
    Lin, CS
    IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE, 1998, : 1119 - 1124
  • [4] Self-organized significance analysis on automatically generated training data for neural networks
    Birkenfeld, Sven
    2014 WORLD AUTOMATION CONGRESS (WAC): EMERGING TECHNOLOGIES FOR A NEW PARADIGM IN SYSTEM OF SYSTEMS ENGINEERING, 2014,
  • [5] Analytical investigation of self-organized criticality in neural networks
    Droste, Felix
    Do, Anne-Ly
    Gross, Thilo
    JOURNAL OF THE ROYAL SOCIETY INTERFACE, 2013, 10 (78)
  • [6] Self-organized criticality in a model for developing neural networks
    Benjamin van den Akker
    Borja Ibarz
    Raoul-Martin Memmesheimer
    BMC Neuroscience, 12 (Suppl 1)
  • [7] Self-organized Operational Neural Networks with Generative Neurons
    Kiranyaz, Serkan
    Malik, Junaid
    Abdallah, Habib Ben
    Ince, Turker
    Iosifidis, Alexandros
    Gabbouj, Moncef
    NEURAL NETWORKS, 2021, 140 (140) : 294 - 308
  • [8] Self-organized noise resistance of oscillatory neural networks with spike timing-dependent plasticity
    Oleksandr V. Popovych
    Serhiy Yanchuk
    Peter A. Tass
    Scientific Reports, 3
  • [9] Self-organized noise resistance of oscillatory neural networks with spike timing-dependent plasticity
    Popovych, Oleksandr V.
    Yanchuk, Serhiy
    Tass, Peter A.
    SCIENTIFIC REPORTS, 2013, 3
  • [10] A Self-Organized Neural Comparator
    Luduena, Guillermo A.
    Gros, Claudius
    NEURAL COMPUTATION, 2013, 25 (04) : 1006 - 1028
12345