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This paper addresses the problem of speech quality enhancement and acoustic noise reduction by adaptive blind source separation algorithms. Recently, several two-channel forward-and-backward structures have been proposed for acoustic noise reduction based on normalized least-mean-square (NLMS) algorithm. The backward structure presents the good performance compared with its direct version (forward)...
The synchronization of a unified chaotic system, used to encrypt different types of information signals, is investigated in this paper. In the outset, it is proven that such a system possesses three different types of chaos characterizations depending on a system's parameter, which guarantees a high degree of communication security. Then, the asymptotic convergence of the errors between the states...
This paper presents a novel terminal synergetic control for DC-DC buck converters. Since buck converters have high nonlinearity and uncertainty, an indirect adaptive control is developed based on recently developed synergetic control methodology. Fuzzy systems are used in an adaptive scheme to approximate the system using a nonlinear model while synergetic control guarantees robustness and the use...
This paper deals with the problem of designing a new iterative learning control (ILC) for a class of strict-feedback nonlinear systems subject to both structured and unstructured uncertainties and dynamic disturbances. These systems are assumed to perform the same task repeatedly under alignment condition. Simple learning mechanisms are proposed to approximate the unknown nonlinear state-dependent...
In this paper, a heuristic optimization approach based on Artificial Bee Colony (ABC) algorithm is applied to the extraction of the five electrical parameters of a photovoltaic (PV) module. The proposed approach has several interesting features such as no prior knowledge of the physical system and its convergence is not dependent on the initial conditions. The extracted parameters have been tested...
This paper proposes a fuzzy approximation-based adaptive sliding-mode controller for uncertain nonlinear perturbed underactuated systems. The fuzzy logic system is used for approximating the unknown nonlinear functions. For estimating the parameters of the fuzzy systems and some unknown bounds, a set of adaptation laws are appropriately designed. The boundedness of all signals of the closed-loop system...
In this paper a new variant of the artificial bee colony algorithm is proposed. It is a known fact that any good optimization algorithm requires a good balance between exploring and exploiting prominent regions of the search space. To this end, several modifications of the artificial bee colony basic algorithm are introduced in the proposed version. The efficiency of the algorithm is evaluated against...
Segmentation by using region-based deformable models has known a great success and large domain of applications. In this paper, we propose a fast algorithm to minimise model which combines local fitting energy and global fitting energy. The minimisation via the proposed algorithm avoids solving any Partial Differential Equation PDE. Consequently, there is no need to any stability conditions. Furthermore,...
In this paper, an observer for Switched Linear Systems (SLS) with unknown inputs is designed. LMI conditions, guaranteeing the asymptotic convergence of the observer derived through multiple Lyapunov functions and LMI region. This is done by decoupling a subset of the system states from the unknown inputs and by estimating the states thanks to a like Luenberger observer. Then, an estimator for the...
The aim of this paper is to propose a generalization of our previous work on practical stabilizing method and switched observer for (low power) single switch DC/DC converters. Generally, the subsystems in PWA models that represent these converters do not share any equilibrium or may not have any one, so that, no strict convergence to any average equilibrium is expected. For this reason, we have opted...
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