1ST-ORDER MARKOV MODEL FOR UNDERSTANDING DELTA MODULATION NOISE SPECTRA

A first-order Markov process is used to model the sequence of quantization noise samples in delta modulation. An autocorrelation parameter C in the Markov model controls the shape of the noise spectrum, and as C decreases from 1 to 0 and then to −1, the spectrum changes from a low-pass to a flat, and then to a high-pass characteristic. One can also use the Markov model to predict the so-called out-of-band noise rejection that is obtained when delta modulation is performed with an oversampled input, and the resulting quantization noise is low-pass filtered to the input band. The noise rejection G is a function of C as well as an oversampling factor F and an interesting asymptotic result is that [FORMULA OMITTED] Delta modulation literature has noted the importance of the special G values, F and 2F. These correspond to autocorrelation values of 0 and −1/3. Copyright © 1978 by The Institute of Electrical and Electronics Engineers, Inc.