Results 261 to 270 of about 2,712,723 (299)

Least Squares Formulation of State Estimation

IFAC Proceedings Volumes, 1994
Abstract A general formulation of least squares estimation for dynamic systems is given. An algorithm with a fixed-size estimation window and constraints on states, disturbances, and measurement noise is developed through a probabilistic interpretation of least squares estimation. Specific issues relevant to linear and nonlinear systems are discussed
DOUGLAS ROBERTSON, JAY H. LEE
openaire   +1 more source

Least Squares Estimates and Optimal Classification

Psychometrika, 1955
A simple algebraic development is given showing that criterion estimates derived by usual multiple regression procedures are optimal for personnel classification. It is also shown that, for any assignment of men to jobs, the sum of the multiple regression criterion estimates will equal the sum of the actual criterion scores.
openaire   +2 more sources

Consistent directions for least‐squares estimates

Canadian Journal of Statistics, 1987
AbstractThe least‐squares estimate θn = Xn+yn of the parameter θ in the linear model Yn = Xnθ + ϵn may not be consistent, but there may be directions u such that u'θn tends to u'θ in some sense. This set of directions u has been characterized in two different papers: Drygas (1976) and Wu (1980).
openaire   +1 more source

A neural network least-square estimator

1990 IJCNN International Joint Conference on Neural Networks, 1990
Problems in which the arguments of objective functions are real numbers are considered. Based on the concept of the Hopfield network, a neural network that solves the least-square estimation problem is derived. With this network, the objective function can converge to any inner point of a hypercube, giving a real-valued solution with very great speed ...
Kegin Gao, M. Omair Ahmad, M. N. Srikanta Swamy   +2 more
openaire   +1 more source

SUBSAMPLING LEAST SQUARES AND ELEMENTAL ESTIMATION

2018 IEEE Data Science Workshop (DSW), 2018
In large-scale regression problems where the dimension of the predictors $p$ and number of observations n are large, subsampling is sometimes used to approximate least squares estimates. One approach to this is algorithmic leveraging, which draws a subsample of size $m$ ≪ $n$ from the observations where high leverage observations (according to the ...
openaire   +2 more sources

Recursive least-squares sequence estimation

IBM Journal of Research and Development, 1994
A family of adaptive communication receivers based on recursive least-squares sequence estimation (RLSSE) algorithms is proposed which provides performance comparable to that of conventional linear receivers, but with reduced complexity and less sensitivity to channel mismatch.
openaire   +2 more sources

Robustness of the least squares range estimator

2016 Australian Communications Theory Workshop (AusCTW), 2016
We consider the problem of distance, or range, estimation by measuring the phase of a sinusoidal signal transmitted between two locations. The distance can only be unambiguously measured if it is contained in an interval of length less than the wavelength of the signal.
Assad Akhlaq, Robby G. McKilliam, André Pollok   +2 more
openaire   +2 more sources

Multistate least-squares parameter estimators

IEEE Transactions on Automatic Control, 1975
Multistage least-squares parameter estimation algorithms which are either recursive in the dimension of an assumed linear model, or both recursive in the model dimension and sequential in time are obtained. Different aspects of the following problems are considered.
openaire   +1 more source

The robust generalized least-squares estimator

Signal Processing, 1992
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +1 more source

The Existence of Moments of the Ordinary Least Squares and Two-Stage Least Squares Estimators

Econometrica, 1972
This paper deals with two single-equation estimators in a set of simultaneous linear stochastic equations--namely, ordinary least squares (OLS) and two-stage least squares (2SLS). Under the assumption that all predetermined variables in the model are exogenous, necessary and sufficient conditions are obtained for the existence of even moments of the ...
openaire   +2 more sources