Because that wavelet transform can effectively extract the characters, the Adaptive Resonance Theory (ART) Neural Networks has a good learning ability.
由于小波变换能有效地提取字符的结构特征，自适应共振(art)网络有很好的学习能力。
This paper combines the two aspects to recognize handwritten digits by using wavelet transform to extract feature and Adaptive Resonance Theory (ART) Neural Networks for Classification.
本文将二者结合起来，用小波变换抽取特征、用自适应共振art网络作模式分类器来识别手写数字。
This fuzzy neural network USES wavelet basis function as membership function whose shape can be adjusted on line so that the networks have better learning and adaptive ability.
这种模糊神经网络利用了小波基函数作为隶属函数，可在线根据误差调整隶属函数的形状，使模糊神经网络具有更强的学习和适应能力。
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