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Inference in Credal Networks with BranchAndBound Algorithms
 IN INT. SYMP. ON IMPRECISE PROBABILITIES AND THEIR APPLICATIONS
, 2003
"... A credal network associates sets of probability distributions with directed acyclic graphs. Under strong independence assumptions, inference with credal networks is equivalent to a signomial program under linear constraints, a problem that is NPhard even for categorical variables and polytree mo ..."
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Cited by 11 (1 self)
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A credal network associates sets of probability distributions with directed acyclic graphs. Under strong independence assumptions, inference with credal networks is equivalent to a signomial program under linear constraints, a problem that is NPhard even for categorical variables and polytree models. We describe
Automated design of operational transconductance amplifiers using reversed geometric programming
 In Proceedings of the 41th IEEE/ACM Design Automation Conference
, 2004
"... We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and nonconvex constraints. Adding a limited set of nonconvex constraints can improve the accuracy of convex equationbased optimizati ..."
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Cited by 3 (0 self)
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We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and nonconvex constraints. Adding a limited set of nonconvex constraints can improve the accuracy of convex equationbased optimization, without compromising global optimality. These constraints allow increased accuracy for critical modeling equations, such as the relationship between gm and IDS. To demonstrate the design methodology, a foldedcascode amplifier is designed in a 0.18 µm technology for varying speed requirements and is compared with simulations and designs obtained from geometric programming. Categories and Subject Descriptors:
A generalization of Pólya’s theorem to signomials with rational exponents, in preparation. See draft at www.math.lsu.edu/∼preprints
"... Pólya proved that if a real, homogeneous polynomial is positive on the nonnegative orthant (except at the origin), then it is the quotient of two homogeneous polynomials with no negative coefficients. We generalize this from polynomials to signomials with arbitrary rational exponents; we also show t ..."
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Cited by 1 (1 self)
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Pólya proved that if a real, homogeneous polynomial is positive on the nonnegative orthant (except at the origin), then it is the quotient of two homogeneous polynomials with no negative coefficients. We generalize this from polynomials to signomials with arbitrary rational exponents; we also show that Pólya’s theorem does not generalize to arbitrary signomials (i.e., with irrational (real) exponents). 1
jpvQeecs.berkeley.edu
"... We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and nonconvex constraints. Adding a limited set of nonconvex constraints can improve the accuracy of convex equationbased optimizati ..."
Abstract
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We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and nonconvex constraints. Adding a limited set of nonconvex constraints can improve the accuracy of convex equationbased optimization, without compromising global optimality. These constraints allow increased accuracy for critical modeling equations, such as the relationship between gm and Ips. To demonstrate the design methodology, a foldedcascode amplifier is designed in a 0.18'pm technology for varying speed requirements and is compared with simnlations and designs obtained from geometric programming. Categories and Subject Descriptors:
10.1 Automated Design of Operational Transconductance Amplifiers using Reversed Geometric Programming
"... We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and nonconvex constraints. Adding a limited set of nonconvex constraints can improve the accuracy of convex equationbased optimizati ..."
Abstract
 Add to MetaCart
We present a method for designing operational amplifiers using reversed geometric programming, which is an extension of geometric programming that allows both convex and nonconvex constraints. Adding a limited set of nonconvex constraints can improve the accuracy of convex equationbased optimization, without compromising global optimality. These constraints allow increased accuracy for critical modeling equations, such as the relationship between gm and IDS. To demonstrate the design methodology, a foldedcascode amplifier is designed in a 0.18 µm technology for varying speed requirements and is compared with simulations and designs obtained from geometric programming. Categories and Subject Descriptors: