Mohamed Anouar El Kamel

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In this paper we describe a fuzzy logic-based language processing method, which is applied to speech recognition. Our purpose is to create a system that can learn from a linguistic corpus the fuzzy semantic relations between the concepts represented by words and use such relations to process the word sequences generated by speech recognition systems. In(More)
This paper treats with the issue of disturbances, noises, uncertainties and sensor faults estimation for uncertain nonlinear systems whose nonlinearity satisfies the Lipschitz condition. The general idea of this approach is to establish an augmented model by supposing the sensor faults as an auxiliary state. In order to ensure the robustness of the proposed(More)
This paper presents a scheme for simultaneously estimating state and sensor fault for a class of uncertain nonlinear systems whose nonlinear function satisfies the Lipschitz condition with unknown inputs and time-varying uncertainties. The effects of the system unknown input and the sensor fault derivative on the estimation errors of states are reduced by(More)
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