1·Methods based on spatial frequencies evaluate the coefficients of the autocorrelation function of the texture.
基于空间频率的方法估计纹理的自相关函数。
2·The spatial autocorrelation analysis has wide applications in many fields, but lacking of corresponding software at present.
空间自相关分析有着广泛的应用领域，但目前缺乏相对的应用软件。
3·This paper introduced a method availing autocorrelation functions to estimate the image fractal dimension, and the method can detect classification of the wood texture.
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。
4·A method extracting multiple target feature by the eigenvalues decomposition of target echo autocorrelation matrix is presented.
提出了基于目标回波自相关矩阵本征值分解提取多目标特征的新方法。
5·The endpoint detection based on short-time average magnitude of speech signals relative autocorrelation sequences can be detected in high accuracy under the low signal-to noise ratio.
在较低信噪比情况下，基于语音信号的短时相对自相关序列的短时平均幅度的端点检测能够获得较高的检测精度。
1·Economic time series is of obvious memory, represent as the series have remarkable autocorrelation, even apart of many spacing, the historical events would influence future events for a long time.
经济时间序列具有非常明显的记忆性，表现为即使相距较远的时间间隔，序列仍然具有显著的自相关性。