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New algorithms for the design of trellis encoding data compression systems are described. The mare algorithm uses a training sequence of actual data from a source to improve an initial trellis decoder. An additional algorithm extends the constraint length of a given decoder. Combined, these algorithms allow the automatic design of a trellis encoding system for a particular source. The algorithms' effectiveness for random sources is demonstrated through performance comparisons with other source coding systems and with theoretical bounds. The algorithms are applied to the practical problem of the design of trellis and hybrid codes for medium-to-lowrate speech compression.
Stewart et al. (Thu,) studied this question.