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dc.contributor.authorChikalov, Igor
dc.date.accessioned2015-08-03T09:02:00Z
dc.date.available2015-08-03T09:02:00Z
dc.date.issued2011
dc.identifier.isbn9783642226601
dc.identifier.issn18684394
dc.identifier.doi10.1007/978-3-642-22661-8_3
dc.identifier.urihttp://hdl.handle.net/10754/561673
dc.description.abstractA Boolean or discrete function can be represented by a decision tree. A compact form of decision tree named binary decision diagram or branching program is widely known in logic design [2, 40]. This representation is equivalent to other forms, and in some cases it is more compact than values table or even the formula [44]. Representing a function in the form of decision tree allows applying graph algorithms for various transformations [10]. Decision trees and branching programs are used for effective hardware [15] and software [5] implementation of functions. For the implementation to be effective, the function representation should have minimal time and space complexity. The average depth of decision tree characterizes the expected computing time, and the number of nodes in branching program characterizes the number of functional elements required for implementation. Often these two criteria are incompatible, i.e. there is no solution that is optimal on both time and space complexity. © Springer-Verlag Berlin Heidelberg 2011.
dc.publisherSpringer Nature
dc.titleRepresenting Boolean Functions by Decision Trees
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.identifier.journalAverage Time Complexity of Decision Trees
kaust.personChikalov, Igor


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