Buscar
Mostrando ítems 1-10 de 1884
Adaptive arrival cost update for improving Moving Horizon Estimation performance
(Elsevier Science Inc, 2017-05)
Moving horizon estimation is an efficient technique to estimate states and parameters of constrained dynamical systems. It relies on the solution of a finite horizon optimization problem to compute the estimates, providing ...
MAP speaker adaptation of state duration distributions for speech recognition
(2002)
This paper presents a framework for maximum a posteriori (MAP) speaker adaptation of state duration distributions in hidden Markov models (HMM). Four key issues of MAP estimation, namely analysis and modeling of state ...
Robust stability of moving horizon estimation for non-linear systems with bounded disturbances using adaptive arrival cost
(Institution of Engineering and Technology, 2020-12)
The robust stability and convergence to the true state of a moving horizon estimator based on an adaptive arrival cost are established for non-linear detectable systems in this study. Robust global asymptotic stability is ...
An application of particle filter for FDI oriented change detection and bounded parameter estimation
(IEEE, 2007)
In their original formulations, state estimation schemes such as Kalman Filter, do not allow the incorporation of prior information on their physical bounds. This results in a certain probability of generating estimates ...
Endogeneity in adaptive choice contexts: Choice-based recommender systems and adaptive stated preferences surveys
(Elsevier, 2020)
Endogeneity arises in discrete choice models due to several factors and results in inconsistent estimates of the model parameters. In adaptive choice contexts such as choice-based recommender systems and adaptive stated ...
Fault section estimation in power systems using an Adaptive Genetic Algorithm
(2016-11-10)
This paper proposes a methodology based on the unconstrained binary programming (UBP) model and an Adaptive Genetic Algorithm (AGA) to solve the fault section estimation problem in power systems. The UBP model is formulated ...
Fault Section Estimation in Power Systems Using an Adaptive Genetic Algorithm
(Ieee, 2016-01-01)
This paper proposes a methodology based on the unconstrained binary programming (UBP) model and an Adaptive Genetic Algorithm (AGA) to solve the fault section estimation problem in power systems. The UBP model is formulated ...
Robust stability of moving horizon estimation for nonlinear systems with bounded disturbances using adaptive arrival cost
(Cornell University, 2019-06)
In this paper, the robust stability and convergence to the true state of moving horizon estimator based on an adaptive arrival cost are established for nonlinear detectable systems. Robust global asymptotic stability is ...
Multiple model approach for robust state estimation in presence of model uncertainty and bounded disturbances
(Cornell University, 2019-06)
In the present work, an optimization-based algorithm for state estimation under model uncertainty and bounded disturbances is presented. In order to avoid to solve a non-convex optimization problem, model and state estimation ...
Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010)
We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton`s method for minimizing a cost function. The proposed solution is formulated to ameliorate the ...