Title :
Quantization errors of modulo sigma-delta modulated ARMA processes
Author :
Li Li ; Yudong Chen
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
In this paper, we study the quantization errors of modulo sigma-delta modulated finite, asymptotically-infinite, infinite causal stable ARMA processes. We show 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 and the asymptotic convergence of quantization errors for some quasi-stationary processes, for different cases. But the assumption of the smooth density of the sampled random processes is needed in all the cases.
Keywords :
autoregressive moving average processes; convergence; quantisation (signal); random processes; signal resolution; asymptotic convergence; asymptotically-infinite processes; high-enough quantization resolution; infinite causal stable processes; modulo sigma-delta modulated finite causal stable ARMA processes; normalized quantization error; quasi-stationary processes; sampled random processes; smooth density; uniformly distributed white noise; Noise; Principal component analysis; Quantization (signal); Random variables; Sigma-delta modulation; Signal resolution; Stochastic processes; ARMA process; Quantization error;
Conference_Titel :
Signal and Information Processing (ChinaSIP), 2013 IEEE China Summit & International Conference on
Conference_Location :
Beijing
DOI :
10.1109/ChinaSIP.2013.6625303