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This talk considers the distributed sparse identification problem over wireless sensor networks such that all sensors cooperatively estimate the unknown sparse parameter vector of stochastic dynamic s...
This paper shows that the performance of a Gaussian Mixture Model using a Universal Background Model (GMM-UBM) speaker verification (SV) system can be further improved by combining it with threshold a...
A method is presented for parameter set estimation for a system which contains both parametric and nonparametric uncertainty. Prior information is available about both types of uncertainty, but only t...
A method is presented for parameter set estimation where the system model is assumed to contain both parametric and nonparametric uncertainty. In the disturbance-free case, the parameter set estimate ...
The paper discusses two methods of optimal excitation signal design for identification with Maximum Likelihood parameter estimation: The ‘classical’, dispersion function based method, and a new, semid...
We consider a mixed linear system model, with both continuous and discrete inputs and outputs, described by a coefficient matrix and a set of noise variances. When the discrete inputs and outputs are ...
First-order SODE: OU processdX+aX(t)dt= dW(t) Three options:a >0, a= 0, a <0. First-order SPDE:du= au xx dt+dW(t, x) One option:a >0(Infinite-dimensional stable OU process.) Second-order SODE:X¨ ...
We servey a series of investigations of optimal testing of multiple hypotheses conserning various multiobject models. These studies are a bright instance of application of methods and technics develop...
The aim of this paper is to provide a fast and efficient procedure for (real-time) target identification in imaging based on matching on a dictionary of precomputed generalized polarization tensors (G...
This paper proposes a new algorithm for linear system identification from noisy measurements. The proposed algorithm balances a data fidelity term with a norm induced by the set of single pole filters...
Abstract: In this paper we consider an inverse problem for the time dependent linear Boltzmann equation. It concerns the identification of the coefficients via a finite number of measurements on the b...
Abstract: T. Saito and M. Teragaito asked in their paper whether Berge knots of type VII, which can be situated on the fiber surface of the lefthand trefoil, are hyperbolic, and showed that some infin...
In this paper a set of formulations of an N-dimensional (ND) autoregressive-moving average (ARMA) model identification method, and a two-dimensional (2D) forgetting factor approach in time-series mode...
A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined ...
This paper proposes a new framework for the optimization of excitation inputs for system identification. The optimization problem considered is to maximize a reduced Fisher information matrix in any o...

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