9,134 research outputs found
An information theory for preferences
Recent literature in the last Maximum Entropy workshop introduced an analogy
between cumulative probability distributions and normalized utility functions.
Based on this analogy, a utility density function can de defined as the
derivative of a normalized utility function. A utility density function is
non-negative and integrates to unity. These two properties form the basis of a
correspondence between utility and probability. A natural application of this
analogy is a maximum entropy principle to assign maximum entropy utility
values. Maximum entropy utility interprets many of the common utility functions
based on the preference information needed for their assignment, and helps
assign utility values based on partial preference information. This paper
reviews maximum entropy utility and introduces further results that stem from
the duality between probability and utility
Growth models on the Bethe lattice
I report on an extensive numerical investigation of various discrete growth
models describing equilibrium and nonequilibrium interfaces on a substrate of a
finite Bethe lattice. An unusual logarithmic scaling behavior is observed for
the nonequilibrium models describing the scaling structure of the infinite
dimensional limit of the models in the Kardar-Parisi-Zhang (KPZ) class. This
gives rise to the classification of different growing processes on the Bethe
lattice in terms of logarithmic scaling exponents which depend on both the
model and the coordination number of the underlying lattice. The equilibrium
growth model also exhibits a logarithmic temporal scaling but with an ordinary
power law scaling behavior with respect to the appropriately defined lattice
size. The results may imply that no finite upper critical dimension exists for
the KPZ equation.Comment: 5 pages, 5 figure
A Wideband 77-GHz, 17.5-dBm Fully Integrated Power Amplifier in Silicon
A 77-GHz, +17.5 dBm power amplifier (PA) with fully integrated 50-Ω input and output matching and fabricated in a 0.12-µm SiGe BiCMOS process is presented. The PA achieves a peak power gain of 17 dB and a maximum single-ended output power of 17.5 dBm with 12.8% of power-added efficiency (PAE). It has a 3-dB bandwidth of 15 GHz and draws 165 mA from a 1.8-V supply. Conductor-backed coplanar waveguide (CBCPW) is used as the transmission line structure resulting in large isolation between adjacent lines, enabling integration of the PA in an area of 0.6 mm^2. By using a separate image-rejection filter incorporated before the PA, the rejection at IF frequency of 25 GHz is improved by 35 dB, helping to keep the PA design wideband
Transformations and 3D Black Hole
We generalize the results of a previous paper by one of the authors to show a
relationship among a class of string solutions through
transformations. The results are applied to a rotating black hole solution of
three dimensional general relativity discussed recently. We extend the black
hole solution to string theory and show its connection with the three
dimensional black string with nonzero momentum through an transformation of the above type.Comment: 12 pages, LaTeX, (December 1992
A New Superconformal Algebra
It is shown that the previously known and superconformal algebras
can be contracted consistently by singular scaling of some of the generators.
For the later case, by a contraction which depends on the central term, we
obtain a new superconformal algebra which contains an Kac-Moody subalgebra and has nonzero central extension.Comment: 10 pages, Latex, IP/BBSR/92-9
On the Capacity Bounds of Undirected Networks
In this work we improve on the bounds presented by Li&Li for network coding
gain in the undirected case. A tightened bound for the undirected multicast
problem with three terminals is derived. An interesting result shows that with
fractional routing, routing throughput can achieve at least 75% of the coding
throughput. A tighter bound for the general multicast problem with any number
of terminals shows that coding gain is strictly less than 2. Our derived bound
depends on the number of terminals in the multicast network and approaches 2
for arbitrarily large number of terminals.Comment: 5 pages, 5 figures, ISIT 2007 conferenc
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