Study on pattern recognition model based on principal component analysis and radius basis function neural network

A pattern recognition model was proposed. Firstly, the theories of principal component analysis and radius basis function neural network were introduced. By the method of principal component analysis, the principal components influencing the pattern recognition were extracted. Based on the analysed results, the model of pattern recognition based on principal component analysis and radius basis function neural network was established. Then it was applied to classify 20 wear particles. And the accuracy of recognition reached 91.3%. The result indicates that this model could get faster speed and higher accuracy, and is worthy of further study and wide use.