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Автор: Tomas Arredondo
Год: 2010
Издание:
LAP Lambert Academic Publishing
Страниц: 264
ISBN: 9783838337104
This work refers to studies on information-theoretic (IT) aspects of data-sequence patterns and developing discriminant algorithms that enable distinguishing the features of underlying sequence patterns having characteristic, inherent stochastical attributes. Considered in this research are specific details on information-theoretics and entropy considerations vis-a-vis sequence patterns (having stochastical attributes) such as DNA sequences of molecular biology. Applying information-theoretic concepts (essentially in Shannon''s sense), the following distinct sets of metrics are developed and applied in the algorithms developed for data-sequence pattern-discrimination applications: (i) Divergence or cross-entropy algorithms of Kullback-Leibler type and of general Czizar class; (ii) statistical distance measures; (iii) ratio-metrics; (iv) Fisher type linear-discriminant measure; (v) complexity metric based on information redundancy; and a Fuzzy logic based measure. Relevant algorithms...
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