Browsing by Keywords "Kalman filter"
Now showing items 1-8 of 8
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Adaptive tracking of narrowband HF channel response
(Wiley-Blackwell Publishing, 2003)Estimation of channel impulse response constitutes a first step in computation of scattering function, channel equalization, elimination of multipath, and optimum detection and identification of transmitted signals through ... -
Brent–Dubai oil spread: Basic drivers
(Economic Society of Australia Inc., 2021-12)This study aims to assess and quantify the effects of potential economic drivers on the Brent–Dubai price spread using the time-dependent Kalman filtering technique. To understand the pricing mechanism of crude oils, it ... -
The effects of different inflation risk premiums on interest rate spreads
(Elsevier BV, 2004)This paper analyzes how the different types of inflation uncertainty affect a set of interest rate spreads for the UK. Three types of inflation uncertainty - structural uncertainty, impulse uncertainty, and steady-state ... -
Identification of hydrodynamic coefficients of AUV in the presence of measurement biases
(Sage Publications, 2021-11-23)This paper mainly presents the parameter identification method developed from a Least Square Estimation (LSE) algorithm to estimate hydrodynamic coefficients of Autonomous Underwater Vehicle (AUV) in the presence of ... -
Is there a flight to quality due to inflation uncertainty?
(Elsevier BV, 2005)After two types of inflation uncertainty are derived within a time-varying parameter model with GARCH specification, the relationship between inflation uncertainty and interest rates for safe assets is investigated. The ... -
A measure of the informal sector for the Turkish diesel market
(Taylor & Francis, 2021-07-09)Measuring the size of the informal diesel market is important for determining tax revenue losses and identifying inefficiencies in tax policies. The conventional ways of assessing the informal sector entail either not ... -
Robust minimax estimation applied to kalman filtering
(Bilkent University, 2008)Kalman filtering is one of the most essential tools in estimating an unknown state of a dynamic system from measured data, where the measurements and the previous states have a known relation with the present state. It ... -
Time-varying cointegration and the Kalman filter
(Taylor and Francis, 2022)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 ...