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Page 3090 of Mathematical Reviews Vol. , Issue 2003d [page]

2003 Mathematical Reviews  
Then, these results are applied to several models: mechanism design, convex program- ming with convex parametrization, continuous objective functions on compact choice sets, saddle-point problems, problems  ...  Summary: “For a lower semicontinuous (I.s.c.) inequality system on a Banach space, it is shown that error bounds hold, provided every element in an abstract subdifferential of the constraint func- tion  ... 

Decentralized Detection With Censoring Sensors

S. Appadwedula, V.V. Veeravalli, D.L. Jones
2008 IEEE Transactions on Signal Processing  
We show that under a send/no-send constraint on each sensor and when the fusion center has its own observations, the sensor decision rules can be determined independently.  ...  In the censoring approach to decentralized detection, sensors transmit real-valued functions of their observations when "informative" and save energy by not transmitting otherwise.  ...  Under Assumption 2.2, and given a communication-rate constraint to be satisfied, at each sensor, consolidation of no-send intervals into a single no-send interval does not increase the error probability  ... 
doi:10.1109/tsp.2007.909355 fatcat:uala5rei6bajpovoybyd4tlkpu

Convergent Approximate Solving of First-Order Constraints by Approximate Quantifiers [article]

Stefan Ratschan
2002 arXiv   pre-print
However, the quantifiers of the first-order predicate language are an obstacle to allowing approximations to arbitrary small error bounds.  ...  Exactly solving first-order constraints (i.e., first-order formulas over a certain predefined structure) can be a very hard, or even undecidable problem.  ...  So an approximate solution set of a constraint φ under a quantifier choice q * is a potential approximate solution set that contains all solution sets of φ under this quantifier choice q * and any measure  ... 
arXiv:cs/0108013v2 fatcat:m2de2hfpjzgpbamlost4midlky

New methods for calculating $$\alpha $$ BB-type underestimators

Anders Skjäl, Tapio Westerlund
2013 Journal of Global Optimization  
Numerical comparisons are made, based on test functions and a set of randomly generated interval Hessians.  ...  The new methods are based on classical eigenvalue bounds from linear algebra and a more recent result on interval matrices.  ...  Scaling by interval widths is thus equivalent to no scaling on these problems depends on the weights of the maximum error objective and does not hold for average errors.  ... 
doi:10.1007/s10898-013-0057-y fatcat:fenxrv2tmfgnxcd3hahlh4tzqm

Energy-efficient detection in sensor networks

S. Appadwedula, D.L. Jones, V.V. Veeravalli
2003 Sixth International Conference of Information Fusion, 2003. Proceedings of the  
For a given resource constraint, we find that randomization over the choice of measurement and over the choice of when to transmit achieves the best performance (in a Bayesian, Neyman-Pearson, and Ali-Silvey  ...  Our approach is to formulate detection problems with constraints on the expected cost arising from transmission (sensor nodes to a fusion node) and measurement (at each sensor node) to address some of  ...  By the no-point mass assumption, there exists a consolidation from two no-send intervals to one no-send interval that preserves the no-send probability under both hypotheses , , 1.  ... 
doi:10.1109/icif.2003.177316 fatcat:ynpfkm2bebasbcdrdecv7q4muy

Energy-efficient detection in sensor networks

S. Appadwedula, V.V. Veeravalli, D.L. Jones
2005 IEEE Journal on Selected Areas in Communications  
For a given resource constraint, we find that randomization over the choice of measurement and over the choice of when to transmit achieves the best performance (in a Bayesian, Neyman-Pearson, and Ali-Silvey  ...  Our approach is to formulate detection problems with constraints on the expected cost arising from transmission (sensor nodes to a fusion node) and measurement (at each sensor node) to address some of  ...  By the no-point mass assumption, there exists a consolidation from two no-send intervals to one no-send interval that preserves the no-send probability under both hypotheses , , 1.  ... 
doi:10.1109/jsac.2005.843536 fatcat:fnuripbwtrg4lncu47bog7xczm

Continuous Galerkin Schemes for Semi-Explicit Differential-Algebraic Equations [article]

Robert Altmann, Roland Herzog
2021 arXiv   pre-print
., the choice of the discretization of the constraint determines the discretization of the Lagrange multiplier.  ...  For the case of linear constraints, we prove convergence of order r+1 both for the state and the multiplier if piecewise polynomials of order r are used. These results are also verified numerically.  ...  Hence, for this particular test function, the error is of one order higher than the error for the state.  ... 
arXiv:2011.09336v2 fatcat:i3z2uhifirdt5ol3645hledenu

The effect of process design on refiner pulp quality control performance

Johan Sund, Christer Sandberg, Anders Karlström, Göran Thungström, Per Engstrand
2021 Nordic Pulp & Paper Research Journal  
The compromise between reducing the IAE and avoiding creating variation by acting on measurement error has a strong influence on the results.  ...  The following parameters were included: analyser sampling interval, time delay, measurement error magnitude, and latency chest residence time.  ...  The random analysis error depends on the choice of pulp property and analysis method.  ... 
doi:10.1515/npprj-2021-0011 fatcat:y6ecnxupk5awhmkcptbdzagpmu

Uncertainty quantification for wide-bin unfolding: one-at-a-time strict bounds and prior-optimized confidence intervals [article]

Michael Stanley, Pratik Patil, Mikael Kuusela
2022 arXiv   pre-print
The OSB intervals are a bin-wise modification of an existing guaranteed-coverage procedure, while the PO intervals are based on a decision-theoretic view of the problem.  ...  These methods are built upon a more general answer to the wide-bin bias problem, involving unfolding with fine bins first, followed by constructing confidence intervals for linear functionals of the fine-bin  ...  Physical Sciences (STAMPS) Research Group and the NSF AI Planning Institute for Data-Driven Discovery in Physics, as well as Amy Braverman, Jonathan Hobbs and Peyman Tavallali, for insightful discussions on  ... 
arXiv:2111.01091v2 fatcat:gbonr5smq5chrfpf3xsg7u7xfy

Tower Pair Selection for Geolocation in 4G Wireless Networks

J.Q. McClintic, M. Tummala, J. McEachen
2013 2013 46th Hawaii International Conference on System Sciences  
Multilateration schemes presented in literature generally focus on deriving a minimum solution.  ...  Given an appropriate choice of geolocation algorithm, it is possible to use graph theory and a few simple facts from linear it is possible to choose index assignments such that geometric dilution of precision  ...  It may be shown that this error is over one hundred times larger than the maximum one-sided error due to timing jitter allowable under the standard given the choice of network parameters reported in Section  ... 
doi:10.1109/hicss.2013.570 dblp:conf/hicss/McClinticTM13 fatcat:o2th5te7pjdxhp3xzrzk46srkm

Accounting for Model Error in Variational Data Assimilation: A Deterministic Formulation

Alberto Carrassi, Stéphane Vannitsem
2010 Monthly Weather Review  
The knowledge of the dynamics, under the form of a model, is unavoidably incomplete and model error affects the prediction accuracy together with the error in the initial condition.  ...  Based on these considerations, a new four-dimensional variational data assimilation (4DVar) weak-constraint algorithm is formulated and tested in the context of a linear unstable system and of the three-component  ...  This work is supported by the Belgian Federal Science Policy Program under Contract MO/34/017.  ... 
doi:10.1175/2010mwr3192.1 fatcat:gigri4dz65glbemtcqjrg6sl4e

Yield statistics of interpolated superoscillations

Eytan Katzav, Ehud Perlsman, Moshe Schwartz
2016 Journal of Physics A: Mathematical and Theoretical  
This is of great importance in any physical system where noise and error are inevitable.  ...  Namely, by how much is the yield decreased when the signal departs from the optimal one. We consider two situations.  ...  Recall that the yield is maximized with respect to the choice of the A m 's under the constraints given by equations (2)-(3). The result is a set of optimal Fourier coefficients à m .  ... 
doi:10.1088/1751-8113/50/2/025001 fatcat:czajf4uvfnbf5dc5oaqp3rg3za

Comparative statics of the generalized maximum entropy estimator of the general linear model

Michael R. Caputo, Quirino Paris
2008 European Journal of Operational Research  
and error values for its implementation.  ...  The generalized maximum entropy method of information recovery requires that an analyst provides prior information in the form of finite bounds on the permissible values of the regression coefficients  ...  Howitt, Martine Quinzii, and seminar participants at the Economic Theory Seminar Series at University of California, Davis for insightful remarks, and two anonymous reviewers for comments on the organization  ... 
doi:10.1016/j.ejor.2006.12.031 fatcat:uiuvlxlxzjh2xlv5kimirz665y

Page 8505 of Mathematical Reviews Vol. , Issue 2001K [page]

2001 Mathematical Reviews  
Luce’s choice rule and without defining a similarity function. It also clarifies the relationship between the MDS choice model and the optimal ver- sion of the identification model based on F. G.  ...  A constraint is an hypothesized inclusion relation on a set of compound relations of restricted length. A constraint set is simply a collection of constraints.  ... 

Worst case additive noise for binary-input channels and zero-threshold detection under constraints of power and divergence

A.L. McKellips, S. Verdu
1997 IEEE Transactions on Information Theory  
We study worst case noise under the criterion of maximum error probability with constraints on both power and divergence with respect to a given symmetric nominal noise distribution.  ...  Particular attention is focused on the cases of a) Gaussian nominal distributions and b) asymptotic increase in worst case error probability when the divergence tolerance tends to zero.  ...  Note thatP = P for = 0 and recall that worst case noise takes the form of a three-point probability mass function under = +1 as discussed in Section II-A.  ... 
doi:10.1109/18.605590 fatcat:4676zz4movfbrmnit3epkw5oty
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