同时，对其解的收敛极限进行了讨论； 并通过实例验证了该算法的有效性。
Discusses the limit of the solution, and proves the effectiveness of the algorithm by examples.
本文讨论了随机序列不具有收敛性时的一般极限行为，一些经典的结果被改进。
Here, general limiting behaviours are discussed when stochastic sequence has no convergence, some classical results are also improved.
我们也证明了K -正则预解算子族的遍历极限的收敛率和逼近的一些结果。
Finally, we obtain some results of the convergence rates of ergodic limits and approximation for K-regularized resolvent families.
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