Fuzzy expert system for interpretable rule extraction from neural networks
Опубликовано: 13-11-2002
Автор(ы): Narayan Srinivasa, Yuri Owechko
Принадлежит: HRL LABORATORIES LLC
Реферат: A method and apparatus for extracting an interpretable, meaningful, and concise rules set from neural networks is presented. The method involves adjustement of gain parameter, μ and the threshold, Tj for the sigmoid activation function of the interactive-or operator used in the extraction/development of a rule set from an artificial neural network. A multi-stage procedure involving coarse (500) and fine adjustment (514) is used in order to constrain the range of the antecedents of the extracted rules to the range of values of the inputs to the artificial neural network. Furthermore, the consequents of the extracted rules are provided based on degree of membership such that they are easily understandable by human beings. The method disclosed may be applied to any pattern recognition task, and is particularly useful in applications such as vehicle occupant sensing and recognition, object recognition, gesture recognition, and facial pattern recognition, among others.
Fuzzy expert system for interpretable rule extraction from neural networks
Номер патента: WO2001061647A3. Автор: Yuri Owechko,Narayan Srinivasa. Владелец: Narayan Srinivasa. Дата публикации: 2002-05-10.