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- W80494675 abstract "Multiple layer feedforward neural networks are often viewed as black boxes as the knowledge stored in the connection weights of these networks is generally considered incomprehensible. This paper suggests a solution to this deficiency of neural networks by proposing a backtracking tree search procedure for converting the weights of a neuron into a symbolic representation and demonstrating its use for understanding and symbolic approximation of feedforward neural networks. Several examples are presented to illustrate the proposed symbolic mapping of neurons." @default.
- W80494675 created "2016-06-24" @default.
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- W80494675 date "1994-01-01" @default.
- W80494675 modified "2023-09-23" @default.
- W80494675 title "Symbolic approximation of feedforward neural networks* *This work was supported in part by the National Science Foundation under Grant IRI-9002087." @default.
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- W80494675 doi "https://doi.org/10.1016/b978-0-444-81892-8.50032-8" @default.
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