Results 21 to 30 of about 75,448 (316)
Journal of Research of the National Bureau of Standards, 1985 The increased power of small computers makes the use of parameter estimation methods attractive. Such methods have a number of uses in analytical chemistry. When valid models are available, many methods work well, but when models used in the estimation are in error, most methods fail.
Brown, Steven D., Rutan, Sarah C.
openaire +3 more sources
Kalman interpolation filter for channel estimation of LTE downlink in high-mobility environments [PDF]
, 2012 The estimation of fast-fading LTE downlink channels in high-speed applications of LTE advanced is investigated in this article. In order to adequately track the fast time-varying channel response, an adaptive channel estimation and interpolation ...
Dai, Xuewu +14 more
core +1 more source
Auto‐calibration Kalman filters for non‐linear systems with direct feedthrough
IET Control Theory & Applications, 2021 The problem of state estimation for non‐linear systems with unknown inputs is discussed. The objective is to construct a non‐linear filter where the unknown input affects both the state equation and measurement equation. An auto‐calibration Kalman filter
Yi Cui, Zhihua Wang
doaj +1 more source
Remote Sensing, 2021 The extended Kalman filter is an extended version of the Kalman filter for a non-linear problem. This study applies this extended Kalman filter to the real-time estimation of the parameters of the dual-pol radar rain rate estimator.
Wooyoung Na, Chulsang Yoo
doaj +1 more source
CoRR, 2021 The Kalman filter is a fundamental filtering algorithm that fuses noisy sensory data, a previous state estimate, and a dynamics model to produce a principled estimate of the current state. It assumes, and is optimal for, linear models and white Gaussian noise. Due to its relative simplicity and general effectiveness, the Kalman filter is widely used in
Beren Millidge +3 more
openaire +2 more sources
TSS-22/demystifying-kalman-filter: First release
, 2023 An attempt at demystifying the Kalman filter, in order to stop making it look more complex than it ...
TSS-22
core +1 more source
Multiplicative Kalman filtering [PDF]
TEST, 2010 We study a non-linear hidden Markov model, where the process of interest is the absolute value of a discretely observed Ornstein-Uhlenbeck diffusion, which is observed after a multiplicative perturbation. We obtain explicit formulae for the recursive relations which link the relevant conditional distributions.
Comte, Fabienne +2 more
openaire +3 more sources
A review: state estimation based on hybrid models of Kalman filter and neural network
Systems Science & Control Engineering, 2023 In this paper, hybrid models of Kalman filter and neural network for state estimation are reviewed of their corresponding academic achievements, the creation of which is a noteworthy development in state estimation.
Shuo Feng +5 more
doaj +1 more source
Friction coefficient estimation using an unscented Kalman filter [PDF]
, 2014 The friction coefficient between a railway wheel and rail surface is a crucial factor in maintaining high acceleration and braking performance of railway vehicles; therefore, monitoring this friction coefficient is important.
Liang, Bo, Zhao, Yunshi, Iwnicki, Simon
core +1 more source
A study on the effects of Kalman Filter on performance of IPMC-Based Active Vibration Control Scheme [PDF]
, 2010 This paper evaluates the effectiveness and performance of Ionic Polymer Metal Composite (IPMC) based active vibration control scheme equipped with the Kalman estimation algorithm.
Bandopadhya, Dibakar +1 more
core +1 more source