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In this paper, an extended linearized neural state space (ELNSS) model is proposed and used to design an approximate pole assignment control strategy for a class of nonlinear systems. At first, the applicability of the ELNSS model to approximate affine nonlinear systems is studied, where the extended Kalman filter (EKF) algorithm is employed to train the weights of the ELNSS model. It has been shown...
An Efficient modeling technique based on immune algorithm and BP neural network is presented for the design of RF MEMS phase shifter. Three sensitive parameters are selected according to complicated three-dimensional structure design of an RF MEMS phase shifter and used as inputs of neural network. In the model, immune algorithm is first used for global search and then BP algorithm for local search...
In this paper, we propose a new fuzzy rule-based system for application in image classification problem. Each rule in our proposed system can represent more than one class. While traditional fuzzy systems consider positive fuzzy rules only, in this paper, we focus on combining negative fuzzy rules with traditional positive ones leading to fuzzy inference systems. This new approach has been tested...
In this paper, a rough set based data mining technique is extended and applied to learn behaviour patterns of moving objects in videos. An intelligent image analysis system is proposed to discover knowledge from video collections. The system is applied to synthetic image sequences containing motions of a predator and prey behaving according to a set of rules. The results show that the system is able...
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