Abstract
Recently, we proposed a new information theory of patterns and forms, namely new measures of the amount of information involved by a given deterministic pattern, and our purpose herein is to examine in which way this approach can be extended in order to fruitfully apply to signal processing. After a short background on the theory, we shall generalize it to distributed maps, and then we shall derive a new concept of informational divergence without probability for patterns and forms, which could be of valuable help to detect change of behaviour in dynamical signals.
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