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» Computing the Pessimism of Inclusion Functions
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RC
2007
83views more  RC 2007»
13 years 4 months ago
Computing the Pessimism of Inclusion Functions
Abstract. “Computing the pessimism” means bounding the overestimation produced by an inclusion function. There are two important distinctions with classical error analysis. Fir...
Gilles Chabert, Luc Jaulin
VLSID
2004
IEEE
111views VLSI» more  VLSID 2004»
14 years 5 months ago
Improved Approach for Noise Propagation to Identify Functional Noise Violations
This paper targets at reducing the crosstalk noise closure time by filtering the set of false violations. We propose two approaches to reduce the pessimism in the crosstalk noise ...
Sachin Shrivastava, Dhanoop Varghese, Vikas Narang...
CORR
2007
Springer
74views Education» more  CORR 2007»
13 years 4 months ago
Secure Two-party Protocols for Point Inclusion Problem
It is well known that, in theory, the general secure multiparty computation problem is solvable using circuit evaluation protocols. However, the communication complexity of the re...
Tony Thomas
ECRTS
2010
IEEE
13 years 4 months ago
The Demand Bound Function Interface of Distributed Sporadic Pipelines of Tasks Scheduled by EDF
—In distributed real-time embedded systems (DRE), it is common to model an application as a set of task chains. Each chain is activated cyclically and must complete before an end...
Nicola Serreli, Giuseppe Lipari, Enrico Bini
EUSFLAT
2007
124views Fuzzy Logic» more  EUSFLAT 2007»
13 years 6 months ago
Mixed Integer Programming, General Concept Inclusions and Fuzzy Description Logics
Fuzzy Description Logics (fuzzy DLs) have been proposed as a language to describe structured knowledge with vague concepts. In [23], a solution based on Mixed Integer Linear Progr...
Umberto Straccia, Fernando Bobillo