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Results for self organizing map r

1. Application of Self-Organizing Maps for clustering DJIA - arXiv

In this paper we apply the Self -Organized Map (SOM) method for clustering the
DJIA and. NASDAQ100 portfolios for determination of non-linear correlations
between stocks. We represent the application of this method as alternative t
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2. Self Organizing Maps: Algorithms and Applications

The stages of the SOM algorithm that achieves this can be summarised as
follows: 1. Initialization – Choose random values for the initial weight vectors wj. 2
. Sampling – Draw a sample training input vector x from the input space. 3.

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3. applications of self- organizing maps - Nova IMS - Universidade

This book is about how the original self- organizing map as well as variants and
extensions of it can be applied in different fields. In fourteen chapters, a wide
range of applications of the Self-Organizing Map is discussed
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4. Application of Self-Organizing Maps to the Maritime - Springer

Finally, an overview of different applications of SOMs in maritime problems is
presented. 1 Introduction. Although the term “Self-Organizing Map” has been
used to designate a number of different entities, it generally refers
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5. A Review of Self-Organizing Map Applications in - InTechOpen

Jan 21, 2011 ... A Review of Self-Organizing Map Applications in Meteorology and
Oceanography. Yonggang Liu and Robert H. Weisberg. College of Marine
Science, University of South Florida. United States of America. 1. Introdu
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6. Engineering Applications of the Self-Organizing Map - IEEE Xplore

works Research Centre, FIN-02150 Espoo, Finland. 1358 tends to manifest
clusters of input information and their relationships on the map. Accordingly, the
most important applications of the SOM are in the visualization of high-

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7. The Self-Organizing Maps: Background, Theories, Extensions and

Various extensions of the SOM have been devised since its introduction to
extend the mapping as effective solutions for a wide range of applications. Its
connections with other learning paradigms and application aspects are
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8. Self Organizing Feature Maps and Their Applications to Robotics

Self Organizing Feature Maps and Their Applications to Robotics. Abstract. The
self-organizing feature maps developed by Kohonen appear to capture some of
the advantages of the natural systems on which t
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9. The Application of Self Organizing Maps in Conceptual Design

The Application of Self. Organizing Maps in Conceptual. Design. Peter C
Matthews. Fitzwilliam College. January 2002. A dissertation submitted for the
Degree of Doctor of Philosophy. Cambridge University Engineering Departmen
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10. self-organizing maps, theory and applications - Nathalie Villa

ABSTRACT. The Self-Organizing Maps (SOM) is a very popular algorithm,
introduced by Teuvo Kohonen in the early 80s. It acts as a non supervised
clustering algorithm as well as a powerful visualization tool. It is widely used
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11. MATLAB Implementation sand Applications of the Self-Organizing Map

Dec 10, 2014 ... MATLAB Implementations and Applications of the. Self-Organizing Map. Teuvo
Kohonen. Aalto University, School of Science. P.O. Box 11000, FI-00076 AALTO,
FINLAND. Unigrafia. Helsinki, Finland, 2014?..
Tags:self organizing map matlab

12. Self-organizing map in Matlab: the SOM Toolbox - CiteSeerX

Abstract. The Self-Organizing Map (SOM) is a vector quantization method which
places the prototype vectors on a regular low-dimensional grid in an ordered
fashion. This makes the SOM a powerful visualization tool. The
Tags:self organizing map matlab

13. Matlab Application of Kohonen Self-organizing Map to Classify

This paper proposes a Matlab object oriented application based on Kohonen Self
- Organizing Maps (SOM) able to classify consumers' daily load profile. Firstly, the
characteristics of Kohonen self- organizing
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14. Publication 6 Self−Organizing Map in Matlab: the SOM Toolbox

Abstract. The Self-Organizing Map (SOM) is a vector quantization method which
places the prototype vectors on a regular low-dimensional grid in an ordered
fashion. This makes the SOM a powerful visualization tool. The
Tags:self organizing map matlab

15. Self-organizing map using matlab Create a Self-Organizing Map

and returns a self-organizing map. • The neurons in the layer of an SOFM are
arranged originally in physical positions according to a topology function. The
function gridtop, hextop, or randtop can arrange the neurons in a grid, he
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16. Using Self-Organizing Maps to Visualize, Filter and - InTechOpen

The self-organizing map (SOM), as a learning algorithm [16], appears to be
suitable for top‐ ology-preserving analysis of ... Using Self-Organizing Maps to
Visualize, Filter and Cluster Multidimensional Bio-Omi
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17. Visual analysis of self-organizing maps - MII

Dec 7, 2011 ... The main objective of self-organizing maps is data clustering and their graphical
presentation. ... Keywords: multidimensional data visualization, self-organizing
map (SOM), visual
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18. Self-Organizing Map in Matlab - Laboratory of Computer and

Self-Organizing Map in Matlab: the SOM Toolbox. Juha Vesanto, Johan Himberg,
Esa Alhoniemi and Juha Parhankangas. Laboratory of Computer and Information
Science. Helsinki University of Technology. P.O.Box 5400, FIN-02
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19. Brief Review of Self-Organizing Maps

Abstract - As a particular type of artificial neural networks, self-organizing maps (
SOMs) are trained using an unsupervised, competitive learning to produce a low-
dimensional, discretized representation of the input space of the
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20. Appetizer: Why use a SOM ?(1/3) - iaria

Self-Organizing Maps. V 1.4 V.Lobo, EN 2010. Example 3: 2D to 2D mapping. ▫
Data uniformly distributed in the square. ▫ Used in the Matlab Demo. [Kohonen
95]. Example 4: 2D to 1D mapping. ▫ Animation. □Red dots=data. □Green
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