Titlebook: Representations of Discrete Functions; Tsutomu Sasao,Masahiro Fujita Book 1996 Kluwer Academic Publishers 1996 CAD.algorithms.complexity.c

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書目名稱Representations of Discrete Functions影響因子(影響力)




書目名稱Representations of Discrete Functions影響因子(影響力)學(xué)科排名




書目名稱Representations of Discrete Functions網(wǎng)絡(luò)公開度




書目名稱Representations of Discrete Functions網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Representations of Discrete Functions被引頻次




書目名稱Representations of Discrete Functions被引頻次學(xué)科排名




書目名稱Representations of Discrete Functions年度引用




書目名稱Representations of Discrete Functions年度引用學(xué)科排名




書目名稱Representations of Discrete Functions讀者反饋




書目名稱Representations of Discrete Functions讀者反饋學(xué)科排名

樣式

輕推

Edge Valued Binary Decision Diagrams, its representation as a pseudo Boolean function. Utilizing this, we present algorithms for computing the probability spectrum and the Reed-Muller spectrum of a Boolean function directly on the .. Finally, we describe an extension of .s which associates both an additive and a multiplicative weight with the true edges of the function graph.

Minikin

Spectral Transform Decision Diagrams,ectively. This chapter shows that an STDD represents a function and its spectral transform at the same time. As for .-bit adders, ACDDs and WDDs require .(.) nodes while MTBDDs require .(2.) nodes. As for .-bit multipliers, ACDDs and WDDs require .(..) nodes while MTBDDs require .(4.) nodes.

Confound

慢跑

magenta

Complexity Theoretical Aspects of OFDDs,the same variable ordering. The replacement of variables by constants may cause an exponential blow-up of the OFDD size. Finally, it is investigated how a local change of the variable ordering may change the OFDD size. This leads to simulated annealing algorithms to improve variable orderings.

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吹牛者

碎石