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E. Ayachi, S. Ihsen and B. Mohamed, “A Comparative Study of Nonlinear Time-Varying Process Modeling Techniques: Application to Chemical Reactor,” Journal of Intelligent Learning Systems and Applications, Vol. 4, No. 1, pp. 20-28.

has been cited by the following article:

• TITLE: Type-2 Fuzzy Extended Kalman Filter for Dynamic Security Monitoring Based on Novel Sensor Fusion

  AUTHORS: Tarek Dakhlallah, Mohammed Zohdy, Omar Salim

  KEYWORDS: Sensor Similarity; Sensor Complementarity; Type-2 Fuzzy

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.4 No.3, August 30, 2012

  ABSTRACT: In this paper, we have focused on several relevant sensors [Laser (for speed measurements), Sonar (for space scanning) and RF (for access rights)] to cooperate in monitoring the security status of multiple dynamic agent in surveillance area. Such coordination is achieved by employing novel concepts of sensors similarity and complementarity. Furthermore, this system is aided with Extended Kalman Filter (EKF) in order to estimate the agent’s non-linear movement. Finally, transforms system state to be able to make a security suspiciousness decision by using type-2 fuzzy logic system to handle uncertainty. It is shown that the system performance can exhibit promising improvements for this dynamic security monitoring application.