In this study, nonlinear neural network controller will be developed to control plasma radial motion in Damavand Tokamak. It is essential to have a good model in order to design a proper controller for plasma radial m...
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In this study, nonlinear neural network controller will be developed to control plasma radial motion in Damavand Tokamak. It is essential to have a good model in order to design a proper controller for plasma radial motion. To achieve this goal, actuator circuits are simulated and in consequence based on simulator model and simulated actuator circuits nonlinear neural network controller will be designed in Damavand Tokamak. Comparison between neural network controller output and PD controller output shows the efficiency of proposed approach.
In this paper the authors propose a structural method for a genetic algorithm (GA) for the optimization problem of cable routing in which cables have to be laid optimally. When there are no limits on the layout routes...
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This paper derives a closed-form expression for the Cramér-Rao bound (CRB) on estimating the source signals in the linear independent component analysis problem, assuming that all independent components have fini...
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This paper derives a closed-form expression for the Cramer-Rao bound (CRB) on estimating the source signals in the linear independent component analysis problem, assuming that all independent components have finite va...
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This paper derives a closed-form expression for the Cramer-Rao bound (CRB) on estimating the source signals in the linear independent component analysis problem, assuming that all independent components have finite variance. It is also shown that the fixed-point algorithm known as FastICA can approach the CRB (the estimate can be nearly efficient) in two situations: (1) when the distribution of the sources is not too much different from Gaussian, for the symmetric version of the algorithm using any of the custom nonlinear functions (pow3, tanh, gauss); (2) when the distribution of the sources is very different from Gaussian (e.g. has long tails) and the nonlinear function in the algorithm equals the score function of each independent component.
The fixed point algorithm, known as FastICA, is one of the most successful algorithms for independent component analysis in terms of accuracy and low computational complexity. This paper derives analytic closed form e...
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The fixed point algorithm, known as FastICA, is one of the most successful algorithms for independent component analysis in terms of accuracy and low computational complexity. This paper derives analytic closed form expressions that characterize separating ability of both one-unit and symmetric version of the algorithm in a local sense. Based on the analysis it is possible to combine advantages of the two versions. Although the analysis assumes a "good" initialization of the algorithms and long data records, our computer simulations demonstrate validity of the theoretical expressions in the case of arbitrary initialization and moderate data lengths
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