Noise covariance matrices in state‐space models: A survey and comparison of estimation methods—Part I
This paper deals with the estimation of the noise covariance matrices of systems described
by state‐space models. Stress is laid on the systematic survey and classification of both the …
by state‐space models. Stress is laid on the systematic survey and classification of both the …
H-infinity filtering for a class of nonlinear discrete-time systems based on unscented transform
W Li, Y Jia - Signal Processing, 2010 - Elsevier
This paper is concerned with the H∞ filtering for a class of nonlinear discrete-time systems.
By embedding the unscented transform technique into the extended H∞ filter structure, the …
By embedding the unscented transform technique into the extended H∞ filter structure, the …
Design of adaptive H∞ filter for implementing on state‐of‐charge estimation based on battery state‐of‐charge‐varying modelling
M Charkhgard, MH Zarif - IET Power Electronics, 2015 - Wiley Online Library
This study suggests a new method for modelling lithium‐ion battery types and state‐of‐
charge (SOC) estimation using adaptive H∞ filter (AHF). First, a universal linear model with …
charge (SOC) estimation using adaptive H∞ filter (AHF). First, a universal linear model with …
Classification of digital amplitude-phase modulated signals in time-correlated non-Gaussian channels
VG Chavali, CRCM da Silva - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
In this paper, a new algorithm is proposed for the classification of digital amplitude-phase
modulated signals in flat fading channels with time-correlated non-Gaussian noise. The first …
modulated signals in flat fading channels with time-correlated non-Gaussian noise. The first …
Discrete-time filtering for nonlinear polynomial systems
This paper presents a suboptimal H∞ filtering problem solution for a class of discrete-time
nonlinear polynomial systems over linear observations. The solution is obtained splitting the …
nonlinear polynomial systems over linear observations. The solution is obtained splitting the …
Reduced-Order Generalized Filtering for Linear Discrete-Time Systems With Application to Channel Equalization
X Li, H Gao - IEEE Transactions on Signal Processing, 2014 - ieeexplore.ieee.org
This paper investigates the problem of reduced-order generalized H_∞ filtering for linear
discrete-time systems. Generalized H_∞ filtering covers standard H_∞ filtering as a special …
discrete-time systems. Generalized H_∞ filtering covers standard H_∞ filtering as a special …
Investigation of the Robust H-Infinity Filter's Effectiveness on the Model Predictive Control and Linear Quadratic Regulator for Active Seismic Control of High-Rise …
Abstract Model predictive control (MPC) strategy uses the current state of a system model to
predict its future behavior in a finite-time horizon. This method minimizes an objective …
predict its future behavior in a finite-time horizon. This method minimizes an objective …
Dual optimal filters for parameter estimation of a multivariate autoregressive process from noisy observations
A Jamoos, E Grivel, N Shakarneh, H Abdel-Nour - IET Signal Processing, 2011 - IET
This study deals with the estimation of a vector process disturbed by an additive white noise.
When this process is modelled by a multivariate autoregressive (M-AR) process, optimal …
When this process is modelled by a multivariate autoregressive (M-AR) process, optimal …
Distributed interacting multiple model H∞ filtering fusion for multiplatform maneuvering target tracking in clutter
W Li, Y Jia - Signal Processing, 2010 - Elsevier
This paper deals with the problem of tracking a single maneuvering target from multiple
platforms in the cluttered environment. A new solution based on H∞ filtering is presented to …
platforms in the cluttered environment. A new solution based on H∞ filtering is presented to …
Jeffrey's divergence between autoregressive processes disturbed by additive white noises
L Legrand, E Grivel - Signal Processing, 2018 - Elsevier
Abstract Jeffrey's divergence (JD), which is the symmetric version of the Kullback–Leibler
divergence, has been used in a wide range of applications, from change detection to clutter …
divergence, has been used in a wide range of applications, from change detection to clutter …