介绍了一种利用自相关函数来估算图像分形维数的方法，并将其应用到木材的纹理分类检测中。
This paper introduced a method availing autocorrelation functions to estimate the image fractal dimension, and the method can detect classification of the wood texture.
多相正交序列的自相关特性非常理想，但在低相数时，互相关特性不够理想。
The properties of auto-correlation for polyphase orthogonal sequences are very ideal, but its cross-correlation properties are not good when the phase number is low.
本文在使用BP神经网络对自相关过程进行监控的基础之上，对隐层神经元数对于神经网络训练收敛性及识别率的影响进行分析研究。
In this research, various number of hidden nodes of neural network is studied to improve the training result and identification capability of BP neural network.
灰度共生矩阵法能够从像元的灰度相关性上对纹理特征进行描述，而分形维数反映了纹理的结构自相似特征。
GLCM describes texture features from pixel correlation of gray and the fractal dimension reflects the structure of self-similar.
灰度共生矩阵法能够从像元的灰度相关性上对纹理特征进行描述，而分形维数反映了纹理的结构自相似特征。
GLCM describes texture features from pixel correlation of gray and the fractal dimension reflects the structure of self-similar.
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