Reordering Transitions in Self—Organized Feature Maps with Short—Range Neighbourhood

ICANN ’94 ◽  
1994 ◽  
pp. 322-325
Author(s):  
R. Der ◽  
M. Herrmann
Keyword(s):  
Short Range ◽  
Feature Maps ◽  
Self Organized

Topological feature maps with self-organized lateral connections: a population-coded, one-layer model of associative memory

1994 ◽  
Vol 72 (2) ◽  
pp. 103-117 ◽  
Author(s):  
Claus Hillermeier ◽  
Niels Kunstmann ◽  
Bernhard Rabus ◽  
Paul Tavan
Keyword(s):  
Associative Memory ◽  
Topological Feature ◽  
Layer Model ◽  
Feature Maps ◽  
Self Organized

ON A COMBINED SHORT-RANGE AND LONG-RANGE INTERACTING EARTHQUAKE MODEL

2000 ◽  
Vol 11 (05) ◽  
pp. 913-919
Author(s):  
A. S. ELGAZZAR ◽  
E. AHMED
Keyword(s):  
Long Range ◽  
Short Range ◽  
Self Organized ◽  
Long Range Interactions ◽  
Earthquake Model

A self-organized critical earthquake model is proposed taking into account the effect of both short-range and long-range interactions. The model obeys both Gutenberg–Richter and Omori laws in addition to being more realistic than other models.

scholarly journals A Hybrid of Self Organized Feature Maps and Parallel Genetic Algorithms for Uncertain Knowledge

2012 ◽  
Vol 60 (6) ◽  
pp. 23-31 ◽  
Author(s):  
Mona Gamal ◽  
Ahmed Abo El-Fatoh ◽  
Shereef Barakat ◽  
Elsayed Radwan
Keyword(s):  
Genetic Algorithms ◽  
Feature Maps ◽  
Parallel Genetic Algorithms ◽  
Self Organized ◽  
Uncertain Knowledge

Phase Transitions in Self-Organized Feature Maps

ICANN ’93 ◽  
1993 ◽  
pp. 597-600
Author(s):  
R. Der ◽  
M. Herrmann
Keyword(s):  
Phase Transitions ◽  
Feature Maps ◽  
Self Organized

Topological feature maps with self-organized lateral connections: a population-coded, one-layer model of associative memory

1994 ◽  
Vol 72 (2) ◽  
pp. 103-117 ◽  
Author(s):  
Claus Hillermeier ◽  
Niels Kunstmann ◽  
Bernhard Rabus ◽  
Paul Tavan
Keyword(s):  
Associative Memory ◽  
Topological Feature ◽  
Layer Model ◽  
Feature Maps ◽  
Self Organized

scholarly journals Cooperative particle rearrangements facilitate the self-organized growth of colloidal crystal arrays on strain-relief patterns

2020 ◽  
Vol 6 (10) ◽  
pp. eaay8418
Author(s):  
Manodeep Mondal ◽  
Chandan K. Mishra ◽  
Rajdeep Banerjee ◽  
Shobhana Narasimhan ◽  
A. K. Sood ◽  
...  
Keyword(s):  
Short Range ◽  
Colloidal Crystal ◽  
The Self ◽  
Surface Structures ◽  
Monolayer Films ◽  
Strain Relief ◽  
Surface Transport ◽  
Self Organized ◽  
Organizational Principle ◽  
Hexagonally Ordered

Strain-relief pattern formation in heteroepitaxy is well understood for particles with long-range attraction and is a routinely exploited organizational principle for atoms and molecules. However, for particles with short-range attraction such as colloids and nanoparticles, which form brittle assemblies, the mechanism(s) of strain-relief is not known. Here, we found that for colloids with short-range attraction, monolayer films on substrates with square symmetry could accommodate large compressive misfit strains through locally dewetted hexagonally ordered stripes. Unexpectedly, over a window of compressive strains, cooperative particle rearrangements first resulted in a periodic strain-relief pattern, which then guided the growth of laterally ordered defect-free colloidal crystals. Particle-resolved imaging of monomer dynamics on strained substrates also helped uncover cooperative kinetic pathways for surface transport. These processes, which substantially influenced the film morphology, have remained unobserved in atomic heteroepitaxy studies hitherto. Leaning on our findings, we developed a heteroepitaxy approach for fabricating hierarchically ordered surface structures.

Self-organized feature maps and information theory

1997 ◽  
Vol 8 (2) ◽  
pp. 215-227 ◽  
Author(s):  
Klaus Holthausen ◽  
Olaf Breidbach
Keyword(s):  
Information Theory ◽  
Feature Maps ◽  
Self Organized

Faithful Representation of Separable Distributions

1997 ◽  
Vol 9 (6) ◽  
pp. 1305-1320 ◽  
Author(s):  
Juan K. Lin ◽  
David G. Grier ◽  
Jack D. Cowan
Keyword(s):  
Geometric Approach ◽  
Data Representation ◽  
Equal Mass ◽  
Distribution Functions ◽  
Faithful Representation ◽  
Feature Maps ◽  
Information Theoretic ◽  
Input Distribution ◽  
Self Organized ◽  
Geometry Problem

A geometric approach to data representation incorporating information theoretic ideas is presented. The task of finding a faithful representation, where the input distribution is evenly partitioned into regions of equal mass, is addressed. For input consisting of mixtures of statistically independent sources, we treat independent component analysis (ICA) as a computational geometry problem. First, we consider the separation of sources with sharply peaked distribution functions, where the ICA problem becomes that of finding high-density directions in the input distribution. Second, we consider the more general problem for arbitrary input distributions, where ICA is transformed into the task of finding an aligned equipartition. By modifying the Kohonen self-organized feature maps, we arrive at neural networks with local interactions that optimize coding while simultaneously performing source separation. The local nature of our approach results in networks with nonlinear ICA capabilities.

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