We combine Tyler's robust estimator of the dispersion matrix with nonlinear shrinkage. This approach delivers a simple and fast in elliptical models that is against both heavy tails high dimensions. prove convergence iterative part our algorithm demonstrate favorable performance wide range simulation scenarios. Finally, an empirical application demonstrates its state-of-the-art on real data.

With regard to the rear-drive in-wheel motor vehicle, this paper studies joint estimation method for vehicle state and road adhesion coefficient. A nonlinear seven degrees of freedom model a tire are established. driving estimator coefficient based on generalized high-order cubature Kalman filter (GHCKF) algorithm designed. The combines calculate parameters, provides parameters estimator, reali...

In this paper we present an MMSE (minimum mean square error) speech feature enhancement algorithm, capitalizing on a new probabilistic, nonlinear environment model that effectively incorporates the phase relationship between the clean speech and the corrupting noise in acoustic distortion. The MMSE estimator based on this phase-sensitive model is derived and it achieves high efficiency by explo...

We present a working implementation of a dynamics based architecture for visual sensing. This architecture provides field rate estimates of the positions and velocities of two independent falling balls in the face of repeated visual occlusions and departures from the field of view. The practical success of this system can be attributed to the interconnection of two strongly nonlinear dynamical ...

In this paper, a novel methodology for state estimation of stochastic dynamical systems is proposed. In this formulation, finite-term Karhunen-Loève (KL) expansion is used to approximate the process noise, thus resulting in a non-autonomous deterministic approximation (with parametric uncertainty) of the original stochastic nonlinear system. It is proved that the solutions of the approximate dy...

A multilayered neural network is a multi-input, multioutput (MIMO) nonlinear system in which training can be regarded as a nonlinear parameter estimation problem by estimating the network weights. In this paper, the relatively new smooth variable structure filter (SVSF) is used for the training of a nonlinear multilayered feed forward network. The SVSF is a recursive sliding mode parameter and ...

Load identification plays an important role in structural health monitoring, which aims at preventing structural failures. In order to identify load for linear systems and nonlinear systems, this paper presents methods to identify load for a cantilever beam based on dynamic strain measurement by Fiber Bragg Grating (FBG) sensors. For linear systems, the proposed inverse method consists of Kalma...

We derive a local linear estimator of generalized impulse response (GIR) functions for nonlinear conditional heteroskedastic autoregressive processes and show its asymptotic normality. We suggest a plug-in bandwidth based on the derived asymptotically optimal bandwidth. A local linear estimator for the conditional variance function is proposed which has simpler bias than the standard estimator....