Abstract
Symbolic signals are, in discrete-time, sequences of quantities that do not assume numeric values. In the most general case, these quantities have no mathematical structure other than that they are members of some set, but they can have a sequential structure. The authors show that processing such signals does not entail mapping them directly to the integers, which would impose more structure-ordering and arithmetic-than present in the data. The authors describe how linear estimation and prediction can be performed on symbolic sequences. They show how spectrograms can be computed from neural population responses and from DNA sequences.
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