Self-organization of a neural network with heterogeneous neurons enhances coherence and stochastic resonance

2009 ◽  
Vol 19 (1) ◽  
pp. 013126 ◽  
Author(s):  
Xiumin Li ◽  
Jie Zhang ◽  
Michael Small
Keyword(s):  
Neural Network ◽  
Stochastic Resonance ◽  
Self Organization

Enhancing threshold neural network via suprathreshold stochastic resonance for pattern classification

2021 ◽  
pp. 127387
Author(s):  
Xiaojie Liu ◽  
Lingling Duan ◽  
Fabing Duan ◽  
François Chapeau-Blondeau ◽  
Derek Abbott
Keyword(s):  
Neural Network ◽  
Stochastic Resonance ◽  
Pattern Classification ◽  
Suprathreshold Stochastic Resonance

scholarly journals Detection of extremely weak NQR signals using stochastic resonance and neural network theories

2018 ◽  
Vol 142 ◽  
pp. 96-103 ◽  
Author(s):  
Weihang Shao ◽  
Jamie Barras ◽  
Panagiotis Kosmas
Keyword(s):  
Neural Network ◽  
Stochastic Resonance

Content-sensitive superpixel segmentation via self-organization-map neural network

2019 ◽  
Vol 63 ◽  
pp. 102572 ◽  
Author(s):  
Murong Wang ◽  
Xiabi Liu ◽  
Nouman Q. Soomro ◽  
Guanhui Han ◽  
Weihua Liu
Keyword(s):  
Neural Network ◽  
Self Organization ◽  
Superpixel Segmentation

Research on the Text Classification Method with Self-Organization Network Model

2011 ◽  
Vol 179-180 ◽  
pp. 940-944
Author(s):  
Jian Chen ◽  
Wen Rong Jiang ◽  
Ji Hong Yan
Keyword(s):  
Neural Network ◽  
National Security ◽  
Network Model ◽  
Text Classification ◽  
Classification Method ◽  
Self Organization ◽  
Crucial Issue ◽  
Text Understanding ◽  
Som Neural Network ◽  
Massive Information

Information retrieval is crucial issue for many areas, like industry, national security, disease control, etc. and how to organize massive information into understandable, readable automatically is a key step to understand data or information. Text Classification is a key issue for automatically text understanding, this paper provides a text classification method based on the SOM neural network model and delivers a reasonable performance.

Entrepreneurial Innovative Network and the Design of Socio-Economic Neural Systems

2020 ◽  
Vol 12 (4) ◽  
pp. 1-23
Author(s):  
Olga Tikhomirova
Keyword(s):  
Neural Network ◽  
Decision Making ◽  
Group Dynamics ◽  
Innovation System ◽  
The Other ◽  
Self Organization ◽  
Neural Systems ◽  
Collective Decision Making ◽  
The World ◽  
The Individual

This article aims to establish how an idea becomes an innovation and how creativity, collective dynamics, and information are interconnected. The results of the author's study showed that the emergence of innovations is closely connected with collective collaboration, and that it is impossible outside of group dynamics. The process of self-organization and collective decision-making is realized through a synergistic interaction, which then transforms into the so-called “information laser” and serves as a basis for the emergence of innovation. Both individuals, as persons and as separate entrepreneurs, are the elements of the innovation system and the actors of the artificial neural network, socio-economic neural systems (SENS-systems). These systems act through self-organization and corporate collaboration, and the efforts of each element are amplified through the interaction with the other elements. The model of the SENS-systems can explain how the individual idea transforms into innovation and spreads throughout the world.

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