arXiv 0908.07942009-08cs.ITcs.NImath.IT

模Sigma-Delta调制ARMA过程的Quantization误差

Quantization Errors of Modulo Sigma-Delta Modulated ARMA Processes

Li Li, Yudong Chen

备注：: An abbreviated version of this paper had been published as Li Li, Yudong Chen, "Quantization errors of modulo sigma-delta modulated ARMA processes," Proceedings of IEEE China Summit & International Conference on Signal and Information Processing, pp. 86-90, 2013
DOI：: 10.1109/ChinaSIP.2013.6625303

摘要：

本文研究了模sigma-delta调制的有限、渐近无穷、无穷因果稳定ARMA过程的量化误差。我们证明了归一化的量化误差可以作为一个均匀分布的白噪声的所有情况下。此外，我们发现，这一良好的性质是由两种不同的机制：足够高的量化分辨率\cite{Bennett1948}和渐近收敛的量化误差的一些准平稳过程\cite{ChouGray1991} - \cite{LiChenLiZhang2009}，对于不同的情况。但在所有情况下都需要假设采样随机过程的密度是光滑的。

英文摘要：

In this paper, we study the quantization errors of modulo sigma-delta modulated finite, asymptotically-infinite, infinite causal stable ARMA processes. We prove that the normalized quantization error can be taken as a uniformly distributed white noise for all the cases. Moreover, we find that this nice property is guaranteed by two different mechanisms: the high-enough quantization resolution \cite{Bennett1948}-\cite{WidrowKollar2008} and the asymptotic convergence of quantization errors for some quasi-stationary processes \cite{ChouGray1991}-\cite{LiChenLiZhang2009}, for different cases. But the assumption of the smooth density of the sampled random processes is needed in all the cases.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。