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614 Chapter 12 APPLICATIONS IN COMMUNICATIONS
FIGURE 12.4
DPCM modified by the linearly filtered error sequence
can also be used for simulation. Develop the following three MATLAB
modules for this project:
1. amodel predictor function to implement (12.12), given the input signal
s(n);
2. a DPCM encoder function to implement the block diagram of Figure
12.3a, which accepts a zero-mean input sequence and produces a
quantized b-bit integer error sequence, where b is a free parameter; and
3. a DPCM decoder function of Figure 12.3b, which reconstructs the signal
from the quantized error sequence.
Experiment with several p-order prediction models for a given signal
and determine the optimum order. Compare this DPCM implementation
with the PCM system of Project 12.1 (at the end of the chapter) and
comment on the results. Extend this implementation to include an mthorder
moving average filter as indicated in (12.16).
12.3 ADAPTIVE PCM AND DPCM (ADPCM)
In general, the power in a speech signal varies slowly with time. PCM
and DPCM encoders, however, are designed on the basis that the speech
signal power is constant, and hence the quantizer is fixed. The efficiency
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