Results 221 to 230 of about 148,393 (248)

ADAPTIVE INPUT ESTIMATION

IFAC Proceedings Volumes, 1990
Abstract An adaptive algorithm for estimating the input to a linear system is presented. This explicite self-tuning filter is based on the identification of an innovations model. From that model, input and measurement noise descriptions are decomposed. Identifiability results guarantee a unique decomposition.
A. Ahlén, M. Sternad
openaire   +1 more source

SIMPLIFIED ADAPTIVE ESTIMATION

IFAC Proceedings Volumes, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yaesh, I., Shaked, U.
openaire   +2 more sources

Adaptive spectral doppler estimation

IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 2009
In this paper, 2 adaptive spectral estimation techniques are analyzed for spectral Doppler ultrasound. The purpose is to minimize the observation window needed to estimate the spectrogram to provide a better temporal resolution and gain more flexibility when designing the data acquisition sequence.
Fredrik, Gran, Andreas, Jakobsson, Jørgen Arendt, Jensen   +2 more
openaire   +2 more sources

Adaptive Multiscale Permeability Estimation

Computational Geosciences, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Grimstad, Alv-Arne, Mannseth, Trond, Nævdal, Geir, Urkedal, Hege   +3 more
openaire   +1 more source

Asymptotically Minimax Adaptive Estimation. II. Schemes without Optimal Adaptation: Adaptive Estimators

Theory of Probability & Its Applications, 1993
See the review in Zbl 0761.62115; and for part I see ibid. 36, No. 4, 645-659 (1991; Zbl 0738.62045).
openaire   +2 more sources

Fast Adaptive Condition Estimation

SIAM Journal on Matrix Analysis and Applications, 1992
The authors present a fast and robust adaptive estimator for the spectral condition number of \(n\) by \(n\) symmetric positive definite matrices \(A_ t\) evolving in time according to rank-one symmetric updates \(A_{t+1}=A_ t+U_ t\) which are performed by updating the Cholesky factor \(R_ t\) or its inverse \(R_ t^{-1}\).
Pierce, Daniel J., Plemmons, Robert J.
openaire   +1 more source

Adaptive distributed estimation

26th IEEE Conference on Decision and Control, 1987
This paper considers the distributed estimation problem when the communication pattern among the agents is not known a priori. We assume a network of estimation agents which receive measurements from the environment. The estimation agents communicate with each other using schedules which may not be fixed a priori.
Chee-yee Chong, Shozo Mori, Kuo-chu Chang   +2 more
openaire   +1 more source

On adaptive estimation

Journal of Statistical Planning and Inference, 1984
Abstract Point estimates that are weighted averages of other estimates are considered. They are adaptive because the weights are also functions of the sample observations.In particular, the weights are functions of new measures of peakedness and skewness.
Robert V. Hogg, Paul S. Horn, Russell V. Lenth   +2 more
openaire   +1 more source

Asymptotically Minimax Adaptive Estimation. I: Upper Bounds. Optimally Adaptive Estimates

Theory of Probability & Its Applications, 1992
The author presents some new solutions of functional adaptive estimation problems arising in stochastic systems with disturbing parameters affecting the accuracy of estimation. The problems considered include estimation of a signal in a Gaussian white noise, estimation of a functional acting on such a signal, prediction in a polynomial regression with ...
openaire   +2 more sources

Adaptive pole estimation

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1990
AN adaptive algorithm is developed for online estimation of the poles of autoregressive (AR) processes. The method estimates the poles directly from the data without intermediate estimation of the AR coefficients or polynomial factorization. It converges rapidly, is computationally efficient, and attains the Cramer-Rao bound (CRB) asymptotically.
A. Nehorai, D. Starer
openaire   +1 more source