Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2006-05-02
2006-05-02
Nguyen-Ba, Antony (Department: 2192)
Data processing: artificial intelligence
Neural network
Learning task
C706S015000
Reexamination Certificate
active
07039621
ABSTRACT:
A method and computer product is presented for mapping n-dimensional input patterns into an m-dimensional space so as to preserve relationships that may exist in the n-dimensional space. A subset of the input patterns is chosen and mapped into the m-dimensional space using an iterative nonlinear mapping process. A set of locally defined neural networks is created, then trained in accordance with the mapping produced by the iterative process. Additional input patterns not in the subset are mapped into the m-dimensional space by using one of the local neural networks. In an alternative embodiment, the local neural networks are only used after training and use of a global neural network. The global neural network is trained in accordance with the mapping produced by the iterative process. Input patterns are initially projected into the m-dimensional space using the global neural network. Local neural networks are then used to refine the results of the global network.
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Agrafiotis Dimitris K.
Lobanov Victor S.
Rassokhin Dmitri N.
Salemme F. Raymond
Johnson & Johnson Pharmaceutical Research & Developmen
Nguyen-Ba Antony
Wilson Sonsini Goodrich & Rosati
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