255,636 research outputs found
An Infeasible-Point Subgradient Method Using Adaptive Approximate Projections
We propose a new subgradient method for the minimization of nonsmooth convex
functions over a convex set. To speed up computations we use adaptive
approximate projections only requiring to move within a certain distance of the
exact projections (which decreases in the course of the algorithm). In
particular, the iterates in our method can be infeasible throughout the whole
procedure. Nevertheless, we provide conditions which ensure convergence to an
optimal feasible point under suitable assumptions. One convergence result deals
with step size sequences that are fixed a priori. Two other results handle
dynamic Polyak-type step sizes depending on a lower or upper estimate of the
optimal objective function value, respectively. Additionally, we briefly sketch
two applications: Optimization with convex chance constraints, and finding the
minimum l1-norm solution to an underdetermined linear system, an important
problem in Compressed Sensing.Comment: 36 pages, 3 figure
Five-dimensional Trinification Improved
We present improved models of trinification in five dimensions. Unified
symmetry is broken by a combination of orbifold projections and a boundary
Higgs sector. The latter can be decoupled from the theory, realizing a
Higgsless limit in which the scale of exotic massive gauge fields is set by the
compactification radius. Electroweak Higgs doublets are identified with the
fifth components of gauge fields and Yukawa interactions arise via Wilson
loops. The result is a simple low-energy effective theory that is consistent
with the constraints from proton decay and gauge unification.Comment: 13 pages LaTeX. v2: reference adde
Design study of a low cost civil aviation GPS receiver system
A low cost Navstar receiver system for civil aviation applications was defined. User objectives and constraints were established. Alternative navigation processing design trades were evaluated. Receiver hardware was synthesized by comparing technology projections with various candidate system designs. A control display unit design was recommended as the result of field test experience with Phase I GPS sets and a review of special human factors for general aviation users. Areas requiring technology development to ensure a low cost Navstar Set in the 1985 timeframe were identified
Reduced-Dimension Linear Transform Coding of Correlated Signals in Networks
A model, called the linear transform network (LTN), is proposed to analyze
the compression and estimation of correlated signals transmitted over directed
acyclic graphs (DAGs). An LTN is a DAG network with multiple source and
receiver nodes. Source nodes transmit subspace projections of random correlated
signals by applying reduced-dimension linear transforms. The subspace
projections are linearly processed by multiple relays and routed to intended
receivers. Each receiver applies a linear estimator to approximate a subset of
the sources with minimum mean squared error (MSE) distortion. The model is
extended to include noisy networks with power constraints on transmitters. A
key task is to compute all local compression matrices and linear estimators in
the network to minimize end-to-end distortion. The non-convex problem is solved
iteratively within an optimization framework using constrained quadratic
programs (QPs). The proposed algorithm recovers as special cases the regular
and distributed Karhunen-Loeve transforms (KLTs). Cut-set lower bounds on the
distortion region of multi-source, multi-receiver networks are given for linear
coding based on convex relaxations. Cut-set lower bounds are also given for any
coding strategy based on information theory. The distortion region and
compression-estimation tradeoffs are illustrated for different communication
demands (e.g. multiple unicast), and graph structures.Comment: 33 pages, 7 figures, To appear in IEEE Transactions on Signal
Processin
- …