Data compression
Abstract
A study of data compression techniques involving linear interpolation
and linear prediction showed that redundancy is a problem that can be
significantly reduced by various polynomial approximations. A more
recent compressor, the continuous secant compressor which determines
the optimum sampling interval prior to sampling, was found to be the most
efficient compressor examined. The continuous secant compressor bases
its reduction technique on a straight-line approximation. Data compression
results when the system in question does not occupy its entire
bandwidth. The addition of white noise over the entire bandwidth was
found to reduce the efficiency of the continuous secant compressor by
only a small amount. The probability distribution of the straight-line
approximation in the presence of noise had a gaussian distribution and a
relatively small standard deviation.
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