A unified framework for connectionist systems (Q1117857)
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scientific article; zbMATH DE number 4093226
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | A unified framework for connectionist systems |
scientific article; zbMATH DE number 4093226 |
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A unified framework for connectionist systems (English)
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1988
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The paper proposes to treat connectionist systems (neural network models) within MAP (maximum a posteriori) estimation framework. The fundamental theorem assigns to every additive dynamical system summarizing function (specifying activity levels of visible neurons X for a given set of connection strengths) the subjective probability function representing the network's belief that X occurs in its environment. Classification and learning processes are then considered and evaluated from this viewpoint for the most popular neural networks paradigms [back-propagation; \textit{M. A. Cohen} and \textit{S. Grossberg} network, IEEE Trans. Syst. Man Cybern. 13, 815-826 (1983; Zbl 0553.92009); Hopfield model].
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maximum likelihood estimation
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MAP estimation
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connectionist systems
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neural network models
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maximum a posteriori
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additive dynamical system summarizing function
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subjective probability function
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Classification
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learning processes
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back-propagation
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\textit{M. A. Cohen} and \textit{S. Grossberg} network
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Hopfield model
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0.8696486
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0.8696394
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0.8651916
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