中文摘要：

这份报纸与使量子化的产量观察和使量子化的输入的一个大班调查 FIR 系统鉴定。出现的 regressors 频率的限制晚辈被采用描绘坚持的刺激，强壮的集中和集中二拍子的圆舞评价算法在下面评价被给的输入。至于 asymptotical 效率，与在算法的 weighting 矩阵的一种合适的选择，尽管 Cram 的产品的限制

英文摘要：

This paper investigates the FIR systems identification with quantized output observations and a large class of quantized inputs. The limit inferior of the regressors＇ frequencies of occurrences is employed to characterize the input＇s persistent excitation, under which the strong convergence and the convergence rate of the two-step estimation algorithm are given. As for the asymptotical efficiency, with a suitable selection of the weighting matrix in the algorithm, even though the limit of the product of the Cramer-Rao （CR） lower bound and the data length does not exist as the data length goes to infinity, the estimates still can be asymptotically efficient in the sense of CR lower bound. A numerical example is given to demonstrate the effectiveness and the asymptotic efficiency of the algorithm.