Then we use the Kalman Filter method(The second one) to do prediction ### Part 2: Call Kalman filter ### #Set Kalman filter parameters x0=0 sigma0=1 phi=1 cQ=1 # These are the Cholesky decomps of Q and R cR=1 # which are the standard devs in this case. #Ksmooth0 returns t...
We show that time-varying parameter state-space models estimated using the Kalman filter are particularly vulnerable to the problem of spurious regression, because the integrated error is transferred to the estimated state equation. We offer a simple yet effective methodology to reliably recover the ...
This work shows an attitude estimator (AE) based on a time-varying Kalman filter (TVKF) and adapted to those cases where a low-acceleration assumption can be applied. This filter is an extended version of a previously published time-varying Kalman filter attitude estimator (TVKAE). A comparat...
kalman filterBeta parameter is used in finance in the form of market model to estimate systematic risk. Such βs are assumed to be time invariant. Literature shows that now there is a considerable evidence that β risk is not constant over time. The aim of this article is the estimation ...
Kalman-filter for time-varying channel estimation in OFDM systems This paper presents the Kalman filter based time-varying channel estimation algorithm for orthogonal frequency divi sion multiplexing(OFDM) systems.Firstly... Y Lei - 《Microcomputer & Its Applications》 被引量: 4发表: 2013年 Robust ...
Our new procedure starts with specifying the time-varying spectrum as a semi-parametric flexible spline function that can be formulated in state space form and can be treated by multivariate Kalman filter and smoothing methods. Next we show how a time series decomposition model can be made ...
A KALMAN FILTER-BASED STABLE DYNAMIC INVERSION FOR DISCRETE-TIME, LINEAR, TIME-VARYING SYSTEMSLinear time-varying systemKalmanˉlterUnknown inputSystem inversionIn this paper the problem of estimating an unknown input for discrete- time, non-minimum phase, multivariable, linear time-varying systems (...
and Wu, H. (2009) `Forecasting the weekly time-varying beta of UK firms: GARCH models vs. Kalman filter method', European Journal of Finance, Vol. 15, No. 4, pp.437-444.Choudhry, T., Wu, H., 2009. Forecasting the weekly time-varying beta of UK firms: GARCH models vs. Kalman ...
We present a robust recursive Kalman filtering algorithm that addresses estimation problems that arise in linear time-varying systems with stochastic parametric uncertainties. The filter has a one-step predictor-corrector structure and minimizes an upper bound of the mean square estimation error at each...
A new algorithm for tracking time-varying fading channels in impulse noise environment is proposed in this paper, which uses the Kalman filter based on Clarke's model. However, the Kalman filter is known t...