In upscaling , to generate an unbiased aggregation of a sparsely sampled variable from an uneven environment , use a richly sampled indicator that covaries with the variable of interest ( a scalar ) to create a weighted average 尺度上推时，要从不规则的环境中建立分散取样变量的无偏集合，就利用与影响变量（标量）共变的已充分取样的指标得到加权平均值。
In the presence of impulsive noise , the two received signals are combinated , so the estimated impulse response of the channel is the eigenvector of its covariation matrix corresponding to the smallest eigenvalue , which can be realized adaptively using generalization of the normalized least mean - norm ( generalized nlmp ) algorithm 该算法在脉冲噪声环境下，组合两个接收信号，使其共变矩阵最小特征值对应的特征向量为信道的估计，并基于广义归一化最小平均范数（广义nlmp ）方法自适应得到该特征向量，从而获得时延估计。
