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On variable ordering of ordered functional decision diagrams
 In GI/GME/ITGFachtagung "Rechnergestützter Entwurf und Architektur mikroelektronischer Systeme"
, 1994
"... In this paper methods for finding good variable orderings for ordered functional decision diagrams (OFDDs) are investigated. We present an algorithm for exact minimization of OFDDs that is applicable for functions up to n = 14 variables. We present an upper bound for the size of OFDDs representing t ..."
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Cited by 1 (1 self)
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In this paper methods for finding good variable orderings for ordered functional decision diagrams (OFDDs) are investigated. We present an algorithm for exact minimization of OFDDs that is applicable for functions up to n = 14 variables. We present an upper bound for the size of OFDDs representing
Satisfiability Problems for Ordered Functional Decision Diagrams
 Universitat Frankfurt
, 1996
"... In this paper we investigate the complexity of problems on Ordered Functional Decision Diagrams (OFDDs) related to satisfiability problems, i.e. SATONE, SATALL and SATCOUNT. We prove that SATALL has a running time linear in the product of the number of satisfying assignments, and the size of the ..."
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Cited by 3 (2 self)
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In this paper we investigate the complexity of problems on Ordered Functional Decision Diagrams (OFDDs) related to satisfiability problems, i.e. SATONE, SATALL and SATCOUNT. We prove that SATALL has a running time linear in the product of the number of satisfying assignments, and the size
Diagrams (OBDDs), Ordered Functional Decision Diagrams (OFDDs) and Ordered (Pseudo) Kronecker Functional Decision
"... The paper presents a family of new expansions of Boolean functions called Functiondriven Linearly Independent (fLI) expansions. On the basis of this expansion a new kind of a canonical representation of Boolean functions is constructed: ..."
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The paper presents a family of new expansions of Boolean functions called Functiondriven Linearly Independent (fLI) expansions. On the basis of this expansion a new kind of a canonical representation of Boolean functions is constructed:
Symbolic Boolean manipulation with ordered binarydecision diagrams
 ACM COMPUTING SURVEYS
, 1992
"... Ordered BinaryDecision Diagrams (OBDDS) represent Boolean functions as directed acyclic graphs. They form a canonical representation, making testing of functional properties such as satmfiability and equivalence straightforward. A number of operations on Boolean functions can be implemented as grap ..."
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Cited by 1036 (13 self)
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Ordered BinaryDecision Diagrams (OBDDS) represent Boolean functions as directed acyclic graphs. They form a canonical representation, making testing of functional properties such as satmfiability and equivalence straightforward. A number of operations on Boolean functions can be implemented
Graphbased algorithms for Boolean function manipulation
 IEEE TRANSACTIONS ON COMPUTERS
, 1986
"... In this paper we present a new data structure for representing Boolean functions and an associated set of manipulation algorithms. Functions are represented by directed, acyclic graphs in a manner similar to the representations introduced by Lee [1] and Akers [2], but with further restrictions on th ..."
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Cited by 3526 (46 self)
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on the ordering of decision variables in the graph. Although a function requires, in the worst case, a graph of size exponential in the number of arguments, many of the functions encountered in typical applications have a more reasonable representation. Our algorithms have time complexity proportional
Efficient implementation of a BDD package
 In Proceedings of the 27th ACM/IEEE conference on Design autamation
, 1991
"... Efficient manipulation of Boolean functions is an important component of many computeraided design tasks. This paper describes a package for manipulating Boolean functions based on the reduced, ordered, binary decision diagram (ROBDD) representation. The package is based on an efficient implementat ..."
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Cited by 504 (9 self)
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Efficient manipulation of Boolean functions is an important component of many computeraided design tasks. This paper describes a package for manipulating Boolean functions based on the reduced, ordered, binary decision diagram (ROBDD) representation. The package is based on an efficient
The Transferable Belief Model
 ARTIFICIAL INTELLIGENCE
, 1994
"... We describe the transferable belief model, a model for representing quantified beliefs based on belief functions. Beliefs can be held at two levels: (1) a credal level where beliefs are entertained and quantified by belief functions, (2) a pignistic level where beliefs can be used to make decisions ..."
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Cited by 489 (16 self)
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and are quantified by probability functions. The relation between the belief function and the probability function when decisions must be made is derived and justified. Four paradigms are analyzed in order to compare Bayesian, upper and lower probability, and the transferable belief approaches.
The pyramid match kernel: Discriminative classification with sets of image features
 IN ICCV
, 2005
"... Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernelbased classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve for correspondenc ..."
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Cited by 544 (29 self)
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Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernelbased classification methods can learn complex decision boundaries, but a kernel over unordered set inputs must somehow solve
An almost ideal demand system.
 American Economic Review,
, 1980
"... Ever since Richard Stone (1954) first estimated a system of demand equations derived explicitly from consumer theory, there has been a continuing search for alternative specifications and functional forms. Many models have been proposed, but perhaps the most important in current use, apart from the ..."
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Cited by 636 (0 self)
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secondorder approximation to any arbitrary direct or indirect utility function or, more rarely, a cost function.
Random Early Detection Gateways for Congestion Avoidance.
 IEEELACM Transactions on Networking,
, 1993
"... AbstractThis paper presents Random Early Detection (RED) gateways for congestion avoidance in packetswitched networks. The gateway detects incipient congestion by computing the average queue size. The gateway could notify connections of congestion either by dropping packets arriving at the gatewa ..."
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Cited by 2716 (31 self)
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at the gateway or by setting a bit in packet headers. When the average queue size exceeds a preset threshold, the gateway drops or marks each arriving packet with a certain probability, where the exact probability is a function of the average queue size. RED gateways keep the average queue size low while
Results 1  10
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