## Abstract

The central theme of this paper is to overcome the inability of feedforward neural networks with hard limiting units to provide confidence evaluation. We consider a Madaline architecture for a 2-group classification problem and concentrate on the probability density function for the neural activation of the first-layer units. As the following layers perform a Boolean table, the expectation value of the output is determined, utilizing the probability of a pattern to perform a definite binary input for the Boolean table. The Madaline architecture can be modified to the introduced Σ-Π-Σ network, which evaluates the expectation value. Several assumptions on the distribution of the neural activation lead to a clear and simple architecture, which is applied to an OCR problem.

Original language | English |
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Pages | 1087-1091 |

Number of pages | 5 |

State | Published - 1997 |

Event | Proceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2) - Ulm, Ger Duration: 18 Aug 1997 → 20 Aug 1997 |

### Conference

Conference | Proceedings of the 1997 4th International Conference on Document Analysis and Recognition, ICDAR. Part 2 (of 2) |
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City | Ulm, Ger |

Period | 18/08/97 → 20/08/97 |