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- Kassem Mustapha, Jaafar AlMutawa
- Numerical Algorithms
- 2012

The numerical solution for a class of fractional sub-diffusion equations is studied. For the time discretization, we use a generalized Crank–Nicolson method combined with the second central finite difference (FD) for the spatial discretization which will then define a fully discrete implicit FD scheme. An error of order O(h 2 max (1, log k − 1) + k 2 + α )… (More)

- Jaafar ALMutawa
- 2008

In this paper, we propose a robust Kalman filter and smoother for the errors-invariables (EIV) state space model subject to observation noise with outliers. We introduce the EIV problem with outliers and then we present the minimum covariance determinant (MCD) estimator which is highly robust estimator to detect outliers. As a result, a new statistical test… (More)

- Jaafar Almutawa
- 21st Mediterranean Conference on Control and…
- 2013

We propose a diagnostic for the state space model fitting time series formed by deleting observations from the data and measuring the change in the estimates of the parameters. A method is proposed for distinguishing an observational outlier from an innovational one. Thus we present a robust subspace system identification algorithm that is less sensitive to… (More)

- Jaafar AlMutawa
- MIM
- 2013

- Jaafar ALMutawa
- 2008

This paper advocates a new subspace system identification algorithm for the errorsin-variables (EIV) state space model via the EM algorithm. To initialize the EM algorithm an initial estimate is obtained by the errors-in-variables subspace system identification method: EIV-MOESP (Chou et al. [1997]) and EIV-N4SID (Gustafsson [2001]). The EM algorithm is an… (More)

- Jaafar AlMutawa
- Int. J. Systems Science
- 2016

- Jaafar AlMutawa
- IMA J. Math. Control & Information
- 2012

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