Stability analysis of feed-forward neural network using topological soliton = 위상솔리톤을 이용한 신경망의 안정성에 관한 연구

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As perceptrons, the generalization power of layered feed-forward neural network(MLP) on the variations in test data is important for practical use of the neural networks. For the analysis of these stabilities in the MLP, we changed the feed-forward of neural network as cascade of $φ^4$ field theory with corresponding field Lagrangian without losing any properties of the network. Using this well-known topological soliton solution of field theory model, the stability of neural network is interpreted as topological stability of kink-type soliton solutions of $φ^4$ field theory. An explicit example, a simple three-class recognition problem, is shown with their theoretical field Lagrangian for practical manner.
Advisors
Koh, In-Gyuresearcher고인규researcher
Description
한국과학기술원 : 물리학과,
Publisher
한국과학기술원
Issue Date
1999
Identifier
151558/325007 / 000973729
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 물리학과, 1999.2, [ ii, 30 p. ]

Keywords

위상적솔리톤해; 안정성; Topological stability; Topological soliton; Field theory; Neural network; 신경망

URI
http://hdl.handle.net/10203/48496
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=151558&flag=dissertation
Appears in Collection
PH-Theses_Master(석사논문)
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