一种基于模糊小波基函数神经网络的图像分类器

A Image Classifier Based on Fuzzy Wavelet Basis Function Neural Network

针对图像分类的特点 ,提出了一种基于模糊小波基函数神经网络的图像分类器。该分类器采用小波基函数作为模糊隶属函数 ,将模糊技术与神经网络相结合 ,利用神经网络实现模糊推理 ,并可对隶属函数的形状进行实时调整 ,从而使分类器具备了更强的学习和自适应能力。实验结果表明 ,这种基于模糊小波基函数神经网络的分类器经过训练后 ,可应用于图像的分类 。

Considering the features of image classification, a image classifier based on fuzzy wavelet basis function neural network is presented. In the classifier, wavelet basis function is used as fuzzy membership function, and fuzzy technique and neural network technique are combined. The fuzzy inference is realized by neural network and the shape of membership function can be adjusted in real time. It endues the classifier with better capability of learning and self adapt. Experimental results show that the fuzzy wavelet basis function neural network classifier can be used in image classification, and its classification precision is superior to that of the conventional maximum likelihood.