H. Mathlouthi

Publications (3)0.56 Total impact

• Article: New approaches to finite impulse response systems identification using higher-order statistics

  K. Abderrahim, H. Mathlouthi, F. Msahli
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  ABSTRACT: In this study, new approaches for the identification of finite impulse response (FIR) systems using higher-order statistics are proposed. The unknown model parameters are obtained using optimisation algorithms. In fact, the proposed method consists first in defining an optimisation problem and second in using an appropriate algorithm to resolve it. Moreover, a new method is developed for estimating the order of FIR models using only the output cumulants. The results presented in this study illustrate the performance of the proposed methods and compare them with a range of existing approaches.
  IET Signal Processing 11/2010; · 0.56 Impact Factor
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  Available from: ntnu.no

  Conference Proceeding: FIR system identification using higher-order statistics

  K. Abederrahim, H. Mathlouthi, F. Msahli
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  ABSTRACT: In this paper, new approaches for the identification of FIR systems using HOS are proposed. The unknown model parameters are obtained using optimization algorithms. In fact, the proposed method consists first in defining an optimization problem and second in using an appropriate algorithm to resolve it. Moreover, we develop a new method for estimating the order of FIR models using only the output cumulants. The results presented in this paper illustrate the performance of our methods and compare them with a range of existing approaches.
  American Control Conference, 2009. ACC '09.; 07/2009
• Conference Proceeding: Optimization approaches for the identification of FIR models using cumulants

  H. Mathlouthi, K. Abderrahim, F. Msahli, G. Favier
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  ABSTRACT: Several methods for the identification of FIR systems using cumulants have been proposed in the literature. These methods can be classified into three categories of solutions: Linear Algebra, Closed form and Optimization. Only linear algebra solutions are considered in this paper. For the sake of simplicity, these methods use the least squares approach to solve a system of equations characterized by a redundant vector of unknown parameters and assumed to be linear, but it not. Mathematically, this approach is not suitable, since the obtained system is nonlinear and must be treated as an optimization problem. To overcome this problem, we define three optimization problems and based on that the best algorithm to solve it will be selected. Simulations are performed to demonstrate the performance of the proposed methods.
  Circuits and Systems for Communications, 2008. ECCSC 2008. 4th European Conference on; 08/2008