From the viewpoint of signal transmission, we studied the SR in summing network constructed by threshold neurons by measuring mutual information and correlation coefficient.
从信号传输的角度出发，我们用互信息和相关系数等指标研究了加和并行阈值神经元网络中的随机共振现象。
Method Under extreme rigid registration condition, correlation coefficient, mutual information and correlation ratio similarity measures were tested as most suitable similarity measures.
方法在极端的刚体配准条件下，检验出互相关系数，互信息和相关比相似性测度为适合的相似性测度。
The stopping time is chosen by minimal mean square error, signal-to-noise ratio and minimal correlation coefficient based on the information of the original (ideal) images and noises.
根据原始图像与噪声的相关信息，应用最小均方误差、信噪比与相关系数最小原则确定微分停止时间。
应用推荐