Permanent link to this recordhttp://hdl.handle.net/10754/561673
MetadataShow full item record
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 . Representing a function in the form of decision tree allows applying graph algorithms for various transformations . Decision trees and branching programs are used for effective hardware  and software  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.
CitationChikalov, I. (2011). Representing Boolean Functions by Decision Trees. Average Time Complexity of Decision Trees, 41–60. doi:10.1007/978-3-642-22661-8_3