Intelligent Database Systems Lab N.Y.U.S. T. I. M. TurSOM: A Turing Inspired Self- organizing Map Presenter: Tsai Tzung Ruei Authors: Derek Beaton, Iren Valova, Dan MacLean IJCNN 2009 國國國國國國國國 National Yunlin University of Science and Technology
Intelligent Database Systems Lab
N.Y.U.S.T.
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
N.Y.U.S.T.
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
N.Y.U.S.T.
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
N.Y.U.S.T.
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
N.Y.U.S.T.
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
N.Y.U.S.T.
I. M.Experiments
Full-featured TurSOM in handwriting experiment typical one-dimensional SOM network
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Intelligent Database Systems Lab
N.Y.U.S.T.
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
N.Y.U.S.T.
I. M.Comment
Advantage Created a more efficient method
Drawback ……
Application SOM
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