本文提出一种以模式聚类为基础的病态样本判定方法，并给出基于模式相似度计算的投票剔除算法。
The author presented a method for morbid sample recognition that base mode clustering, paper proposed a eliminating algorithm of voting that base mode similarity calculating.
提出了一类基于先验信息的时变参数辨识算法以克服病态辨识。
A new identification method based on apriori information is proposed for time varying process to avoid the ill-condition of least squares method.
本文通过对RCA算法中遗忘函数的修正，抑制了类间竞争迭代中的病态发散，从而实现了算法的稳健收敛。
This paper modifies the loss function of RCA algorithm, gets a robust convergence by restraining the ill con- dition in the iteration of competitive agglomeration among the clusters.
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