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The Fibonacci sequence has been generalized in many ways.
The Fibonacci sequence has been generalized in many ways, for example, by changing the initial values, by changing the recurrence relation, and so on.
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The result of Theorem A for independent and identically distributed sequences has been generalized to some dependent sequences, such as negatively associated sequences, negatively superadditive dependent sequences, ρ ˜ -mixing sequences, φ ˜ -mixing sequences, and so forth.
In general, the theorem has been generalized in two directions.
In the two decades since its original proposal, CGR has been generalized beyond its original focus on genomic sequences and has been successfully applied to a wide range of problems in bioinformatics.
For example, it has been generalized to multidimensional vector spaces.
This concept has been generalized to higher-dimensional (coordinate) Euclidean spaces.
This idea has been generalized by considering arbitrary preference relations between models of sets of premises.
This idea has been generalized in Kratzer (1986).
The algorithm has been generalized for application to bioinformatics datasets, including the prediction of splice site junctions in Human DNA sequences.
Since then this notion has been generalized in different directions.
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