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A digital signal processor's data format determines its ability to handle sig-
nals of differing precision, dynamic range, and signal-to-noise ratios.
However, ease-of-use and time-to-market considerations are often equally
important.
Precision. The number of bits of precision of A/D converters has contin-
ued to increase, and the trend is for both precision and sampling rates to
increase.
Dynamic Range. Compression and decompression algorithms have tradi-
tionally operated on signals of known bandwidth. These algorithms were
developed to behave regularly, to keep costs down and implementations
easy. Increasingly, however, the trend in algorithm development is to
unconstrain the regularity and dynamic range of intermediate results.
Adaptive filtering and imaging are two applications that require a wide
dynamic range.
Signal-to-Noise Ratio. Audio, video, imaging, and speech recognition
require wide dynamic range to discern selected signals occurring in noisy
environments.
Ease-of-Use. In general, 32-bit, floating-point DSPs are easier to use and
enable a quicker time-to-market than 16-bit, fixed-point processors. The
extent to which this is true depends on the floating-point processor's
architecture. Consistency with IEEE workstation simulations and the
elimination of scaling are two clear ease-of-use advantages. High-level lan-
guage programmability, large address spaces, and wide dynamic range
enable system development time to focus on algorithms and signal pro-
cessing concerns, rather than assembly language coding, code paging, and
error handling.
1-8
ADSP-21065L SHARC User's Manual
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