Intelligent Database Systems Lab

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I. M.

TurSOM: A Turing Inspired Self-organizing Map

Presenter: Tsai Tzung Ruei 　Authors: Derek Beaton, Iren Valova, Dan MacLean

IJCNN 2009

國立雲林科技大學National Yunlin University of Science and Technology

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Outline

Motivation Objective Methodology Experiments Conclusion Comments Reference Data

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Intelligent Database Systems Lab

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I. M.Motivation

The traditional SOM is slower than TurSOM and need for post-processing methods for cluster identification.

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人腦接受不同外來刺激示意圖

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Objective

To present a new variant of the SOM algorithm that utilizes two forms of selforganization:1) neurons, as in the classical Kohonen algorithm and 2) connections, as presented in Turing's model of Unorganized Machines.

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Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology

TurSOM

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Neuron

ConnectionTuring Unorganized Machines

Competitive Learning Techniques

SOM algorithms

Intelligent Database Systems Lab

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I. M.Methodology

Neuron responsibility Connection responsibility

The gap junction (GJ) mechanism

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NeuronA r NeuronB

Relative bigness

NeuronC

Intelligent Database Systems Lab

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I. M.Methodology

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Algorithmic Explanation

B100

C5

A80

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I. M.Experiments

Early TurSOM and double spiral problem

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PurposeTo test the hypothesis of connection reorganization being beneficial.

Intelligent Database Systems Lab

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I. M.Experiments

Full-featured TurSOM in handwriting experiment TurSOM

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PurposeTo test the full-featured TurSOM on asample from a handwriting dataset

Intelligent Database Systems Lab

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I. M.Experiments

Full-featured TurSOM in handwriting experiment typical one-dimensional SOM network

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Intelligent Database Systems Lab

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I. M.Experiments

TurSOM

1D standardSOM

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random

the Peano-Iike convergencefeaturing single chain

Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Conclusion

MAJOR CINTRIBUTION TurSOM displays behavior of a highly efficient SOM, in terms of both

time and computational expense.

The TurSOM algorithm is applicable in a varying number of fields, just like the traditional SOM, but TurSOM lends itself more so to image processing and segmentation.

No post-processing methods are required in addition to TurSOM to detect distinct patterns, unlike other SOM algorithms, due to TurSOM‘s connection reorganization methods.

FUTURE WORK To take connection reorganization to scale (n-dimensional SOM

networks).

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Intelligent Database Systems Lab

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I. M.Comment

Advantage Created a more efficient method

Drawback ……

Application SOM

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Intelligent Database Systems Lab

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I. M.Reference Data

http://www.im.isu.edu.tw/faculty/pwu/NN/CH06.pptDrawback

http://zh.wikipedia.org/zh-tw/%E5%9B%BE%E7%81%B5%E6%9C%BA

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