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- W2099037996 abstract "We combine neural network and syntactic pattern recognition, and propose a tree automaton system for the recognition of structural seismic patterns in a seismogram. Multilayer perceptron of the neural network is used for the identification of subpatterns, then a tree representation of the structural seismic pattern is constructed. We use three kinds of modified bottom-up structure preserved error correcting tree automata to recognize the tree representation of syntactic pattern, and propose a new top-down error correcting tree automaton to recognize non-structural preserved seismic pattern, in the experiments, the system is applied to the simulated and the real seismic bright spot patterns. The recognition result can improve seismic interpretation." @default.
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- W2099037996 date "2005-01-31" @default.
- W2099037996 modified "2023-09-25" @default.
- W2099037996 title "Neural network and tree automaton for seismic pattern recognition" @default.
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- W2099037996 doi "https://doi.org/10.1109/ijcnn.2004.1379996" @default.
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