Abstract
A method of compressing electroencephalographic signals using the set partitioning in hierarchical trees (SPIHT) algorithm is described. The signals were compressed at a variety of different compression ratios (CRs), with the loss of signal integrity at each CR determined using the percentage root-mean squared difference between the reconstructed signal and the original. An analysis of the computational complexity of the SPIHT algorithm is also presented, using the Blackfin processor as an example implementation target.
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