The Experts below are selected from a list of 21201 Experts worldwide ranked by ideXlab platform
L. Dewey - One of the best experts on this subject based on the ideXlab platform.
-
ICASSP - Seismic velocity Estimators
ICASSP '83. IEEE International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: R. Kirlin, L. DeweyAbstract:The layered subsurface geologic model leads to an approximate hyperbolic curve of delay vs sensor offset distance for seismic signals. Four "optimum" Estimators for the rms seismic velocity are given and analyzed by simulation for rms error. Parameters varied include center-point depth (time), apriori velocity variance and mean, delay-estimate variance and inter-delay-estimate correlation. The maximum likelihood Estimator is shown to be best when apriori information is relatively good, but a least mean Square Estimator is best otherwise.
R. Kirlin - One of the best experts on this subject based on the ideXlab platform.
-
ICASSP - Seismic velocity Estimators
ICASSP '83. IEEE International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: R. Kirlin, L. DeweyAbstract:The layered subsurface geologic model leads to an approximate hyperbolic curve of delay vs sensor offset distance for seismic signals. Four "optimum" Estimators for the rms seismic velocity are given and analyzed by simulation for rms error. Parameters varied include center-point depth (time), apriori velocity variance and mean, delay-estimate variance and inter-delay-estimate correlation. The maximum likelihood Estimator is shown to be best when apriori information is relatively good, but a least mean Square Estimator is best otherwise.
Dipak K Dey - One of the best experts on this subject based on the ideXlab platform.
-
asymptotic properties of marginal least Square Estimator for ultrahigh dimensional linear regression models with correlated errors
The American Statistician, 2019Co-Authors: Gyuhyeong Goh, Dipak K DeyAbstract:In this article, we discuss asymptotic properties of marginal least-Square Estimator for ultrahigh-dimensional linear regression models. We are specifically interested in probabilistic consistency of the marginal least-Square Estimator in the presence of correlated errors. We show that under a partial orthogonality condition, the marginal least-Square Estimator can achieve variable selection consistency. In addition, we demonstrate that if a mutual orthogonality holds, the marginal least-Square Estimator satisfies estimation consistency. The discussed theories are exemplified through extensive simulation studies.
-
asymptotic properties of marginal least Square Estimator for ultrahigh dimensional linear regression models with correlated errors
The American Statistician, 2019Co-Authors: Gyuhyeong Goh, Dipak K DeyAbstract:In this article, we discuss asymptotic properties of marginal least-Square Estimator for ultrahigh-dimensional linear regression models. We are specifically interested in probabilistic consistency ...
O L V Costa - One of the best experts on this subject based on the ideXlab platform.
-
linear minimum mean Square filter for discrete time linear systems with markov jumps and multiplicative noises
Automatica, 2011Co-Authors: O L V Costa, Guilherme R A M BenitesAbstract:In this paper we obtain the linear minimum mean Square Estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean Square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline.
-
optimal linear mean Square filter for continuous time jump linear systems
IEEE Transactions on Automatic Control, 2005Co-Authors: Marcelo D Fragoso, O L V Costa, Jack Baczynski, N RochaAbstract:We consider a class of hybrid systems which is modeled by continuous-time linear systems with Markovian jumps in the parameters (LSMJP). Our aim is to derive the best linear mean Square Estimator for such systems. The approach adopted here produces a filter which bears those desirable properties of the Kalman filter: A recursive scheme suitable for computer implementation which allows some offline computation that alleviates the computational burden. Apart from the intrinsic theoretical interest of the problem in its own right and the application-oriented motivation of getting more easily implementable filters, another compelling reason why the study here is pertinent has to do with the fact that the optimal nonlinear filter for our estimation problem is not computable via a finite computation (the filter is infinite dimensional). Our filter has dimension Nn, with n denoting the dimension of the state vector and N the number of states of the Markov chain.
Min Wang - One of the best experts on this subject based on the ideXlab platform.
-
Trajectory Snakes for Robotic Motion Tracking
2006 International Conference on Mechatronics and Automation, 2006Co-Authors: Xinhan Huang, Min WangAbstract:Robotic motion trajectory maintains continuousness and smoothness in spatial-temporal space. A novel trajectory snake model is proposed for visual tracking of moving manipulator. Snake energy function of robotic motion is defined involving kinematic energy, curve potential and image potential energy. The motion trajectory can be located through searching the converged energy distribution of the snake function. Energy weights in the function are real-time adjusted to avoid local minima during convergence. To improve snake searching efficiency, quadratic-trajectory least Square Estimator is employed to predict manipulator motion position before tracking. A fast visual tracking algorithm based on the trajectory snake model is developed and experimental results of tracking micromanipulator motion demonstrate its performance.