一类基于模糊神经元的复杂非线性化学模式识别方法

A Type of Fuzzy Classification Neural Networks for Complex Nonlinear Chemical Pattern Recognition

针对模式类别边界曲折而模糊的复杂化学模式分类问题 ,提出一种化学模式模糊分类方法 ,并给出其模糊神经元分类器设计和网络训练算法 ,使模糊神经元分类器具有学习功能 .

For a type of classification problems of complex chemical patterns, in which the edges between pattern classes are rather irregular or ill defined, a new fuzzy computing method for chemical pattern classification is proposed. The new method was realized with a fuzzy neural network. An algorithm for training the fuzzy neural networks, which makes the fuzzy pattern classifier has the ability of learning from examples, is given. An example of classifying complex chemical pattern was used to verify the efficiency of the new method.