Displaying similar documents to “On the Complexity of the Hidden Weighted Bit Function for Various BDD Models”

On the Influence of the State Encoding on OBDD-Representations of Finite State Machines

Christoph Meinel, Thorsten Theobald (2010)

RAIRO - Theoretical Informatics and Applications

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Ordered binary decision diagrams are an important data structure for the representation of Boolean functions. Typically, the underlying variable ordering is used as an optimization parameter. When finite state machines are represented by OBDDs the state encoding can be used as an additional optimization parameter. In this paper, we analyze the influence of the state encoding on the OBDD-representations of counter-type finite state machines. In particular, we prove lower bounds,...

Evaluation of decision-making units based on the weight-optimized DEA model

Jiasen Sun, Rui Yang, Xiang Ji, Jie Wu (2017)

Kybernetika

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Data envelopment analysis (DEA) is a methodology for measuring best relative efficiencies of a group of peer decision-making units (DMUs) that take multiple inputs to produce multiple outputs. However, the traditional DEA model only aims to maximize the efficiency of the DMU under evaluation. This usually leads to very small weights (even zero weights) being assigned to some inputs or outputs. Correspondingly, these inputs or outputs have little or even no contribution to efficiency,...

Robust estimation based on spacings in weighted exponential models

Paweł Błażej, Jarosław Bartoszewicz (2007)

Applicationes Mathematicae

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Using Zieliński's (1977, 1983) formalization of robustness Błażej (2007) obtained uniformly most bias-robust estimates (UMBREs) of the scale parameter for some statistical models (including the exponential model), in a class of linear functions of order statistics, when violations of the models are generated by weight functions. In this paper the UMBRE of the scale parameter, based on spacings, in two weighted exponential models is derived. Extensions of results of Bartoszewicz (1986,...