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Recognition of Properties by Probabilistic Neural Networks

机译:通过概率神经网络识别属性

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The statistical pattern recognition based on Bayes formula implies the concept of mutually exclusive classes. This assumption is not applicable when we have to identify some non-exclusive properties and therefore it is unnatural in biological neural networks. Considering the framework of probabilistic neural networks we propose statistical identification of non-exclusive properties by using one-class classifiers.
机译:基于贝叶斯公式的统计模式识别隐含了互斥类的概念。当我们必须确定一些非排他性时,该假设不适用,因此在生物神经网络中是不自然的。考虑到概率神经网络的框架,我们提出使用一类分类器对非排他性进行统计识别。

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