Results 1 to 10 of about 2,319,042 (224)

Robust Relative Error Estimation [PDF]

open access: yesEntropy, 2018
Relative error estimation has been recently used in regression analysis. A crucial issue of the existing relative error estimation procedures is that they are sensitive to outliers. To address this issue, we employ the γ -likelihood function, which is constructed through γ -cross entropy with keeping the original statistical model in use. The
Kei Hirose, Hiroki Masuda
openaire   +4 more sources

Constrained Phase Noise Estimation in OFDM Using Scattered Pilots Without Decision Feedback [PDF]

open access: yes, 2016
In this paper, we consider an OFDM radio link corrupted by oscillator phase noise in the receiver, namely the problem of estimating and compensating for the impairment.
Mathecken, Pramod   +3 more
core   +2 more sources

Errors on errors – Estimating cosmological parameter covariance [PDF]

open access: yesProceedings of the International Astronomical Union, 2014
AbstractCurrent and forthcoming cosmological data analyses share the challenge of huge datasets alongside increasingly tight requirements on the precision and accuracy of extracted cosmological parameters. The community is becoming increasingly aware that these requirements not only apply to the central values of parameters but, equally important, also
Joachimi, Benjamin, Taylor, Andy
openaire   +2 more sources

BER estimation for wireless links using BPSK/QPSK modulation [PDF]

open access: yes, 2003
This paper introduces a method that computes an estimation of the bit error rate (BER) based on the RAKE receiver soft output only. For this method no knowledge is needed about the channel characteristics nor the precise external conditions.
Hurink, Johann L.   +2 more
core   +8 more sources

Signal Estimation with Additive Error Metrics in Compressed Sensing [PDF]

open access: yes, 2013
Compressed sensing typically deals with the estimation of a system input from its noise-corrupted linear measurements, where the number of measurements is smaller than the number of input components.
Danielle Carmon   +4 more
core   +3 more sources

Unified Description of Efficiency Correction and Error Estimation for Moments of Conserved Quantities in Heavy-Ion Collisions [PDF]

open access: yes, 2017
We provide a unified description of efficiency correction and error estimation for moments of conserved quantifies in heavy-ion collisions. Moments and cumulants are expressed in terms of the factorial moments, which can be easily corrected for the ...
Luo, Xiaofeng
core   +1 more source

Local observers on linear Lie groups with linear estimation error dynamics [PDF]

open access: yes, 2013
This paper proposes local exponential observers for systems on linear Lie groups. We study two different classes of systems. In the first class, the full state of the system evolves on a linear Lie group and is available for measurement.
Koldychev, Mikhail, Nielsen, Christopher
core   +2 more sources

Linearization errors in discrete goal-oriented error estimation

open access: yesComputer Methods in Applied Mechanics and Engineering, 2023
This paper is concerned with goal-oriented a posteriori error estimation for nonlinear functionals in the context of nonlinear variational problems solved with continuous Galerkin finite element discretizations. A two-level, or discrete, adjoint-based approach for error estimation is considered.
Brian N. Granzow   +2 more
openaire   +3 more sources

Estimation with Norm Regularization [PDF]

open access: yes, 2015
Analysis of non-asymptotic estimation error and structured statistical recovery based on norm regularized regression, such as Lasso, needs to consider four aspects: the norm, the loss function, the design matrix, and the noise model.
Banerjee, Arindam   +3 more
core  

Error structures and parameter estimation [PDF]

open access: yes, 2006
This article proposes a link between statistics and the theory of Dirichlet forms used to compute errors. The error calculus based on Dirichlet forms is an extension of classical Gauss' approach to error propagation.
Bouleau, Nicolas, Chorro, Christophe
core   +3 more sources

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