100 resultados para Peruvian internal conflict


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In this paper, we show how a set of recently derived theoretical results for recurrent neural networks can be applied to the production of an internal model control system for a nonlinear plant. The results include determination of the relative order of a recurrent neural network and invertibility of such a network. A closed loop controller is produced without the need to retrain the neural network plant model. Stability of the closed-loop controller is also demonstrated.

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Recurrent neural networks can be used for both the identification and control of nonlinear systems. This paper takes a previously derived set of theoretical results about recurrent neural networks and applies them to the task of providing internal model control for a nonlinear plant. Using the theoretical results, we show how an inverse controller can be produced from a neural network model of the plant, without the need to train an additional network to perform the inverse control.

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A particulate microemulsion is generated in a simple two-component system comprising an amphiphilic copolymer (Pluronic P123) in mixtures with tannic acid. This is correlated to complexation between the poly(ethylene oxide) in the Pluronic copolymer and the multiple hydrogen bonding units in tannic acid which leads to the breakup of the ordered structure formed in gels of Pluronic copolymers, and the formation of dispersed nanospheres containing a bicontinuous internal structure. These novel nanoparticles termed ‘‘emulsomes’’ are self-stabilized by a coating layer of Pluronic copolymer. The microemulsion exhibits a pearlescent appearance due to selective light scattering from the emulsion droplets. This simple formulation based on a commercial copolymer and a biofunctional and biodegradable additive is expected to find applications in the fast moving consumer goods sector.