209,985 research outputs found

    Automatic loop-shaping in quantitative feedback theory using genetic algorithms

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    Design automation in Quantitative Feedback Theory (QFT) is addressed in this paper. An automatic loop shaping procedure based on Genetic Algorithms (GAs) is developed, where a robust controller for uncertain plants can be designed automatically such that the cost of feedback is minimised and all robust stability and performance specifcations are satisfed. The developed approach can improve the current QFT design in at least two aspects. One is in the design of an initial controller for complicated plants, which might be difficult even to find a stabilising controller manually. The other is in improving the initial manual design by optimisation of the performance index under the prescribed requirements within the neighbourhood of the manual design. An illustrative example which compares manual loop shaping with automatic loop shaping is presented

    On the Inverse Problem Relative to Dynamics of the w Function

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    In this paper we shall study the inverse problem relative to dynamics of the w function which is a special arithmetic function and shall get some results.Comment: 11 page

    Compression of Deep Neural Networks on the Fly

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    Thanks to their state-of-the-art performance, deep neural networks are increasingly used for object recognition. To achieve these results, they use millions of parameters to be trained. However, when targeting embedded applications the size of these models becomes problematic. As a consequence, their usage on smartphones or other resource limited devices is prohibited. In this paper we introduce a novel compression method for deep neural networks that is performed during the learning phase. It consists in adding an extra regularization term to the cost function of fully-connected layers. We combine this method with Product Quantization (PQ) of the trained weights for higher savings in storage consumption. We evaluate our method on two data sets (MNIST and CIFAR10), on which we achieve significantly larger compression rates than state-of-the-art methods

    Evolutionary computation enabled game theory based modelling of electricity market behaviours and applications

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    The collapse of the Californian electricity market system in 2001 has highlighted urgency in research in intelligent electricity trading systems and strategies involving both suppliers and customs. In their trading systems, power generation companies under the new electricity trading arrangement (NETA) of the UK are now developing gaming strategies. However, modelling of such "intelligent" market behaviours is extremely challenging, because traditional mathematical and computer modelling techniques cannot cope with the involvement of game theory. In this paper, evolutionary computation enabled modelling of such system is presented. Both competitive and cooperative game theory strategies are taken into account in evolving the intelligent model. The model then leads to intelligent trading strategy development and decision support. Experimental tests, verification and validation are carried out with various strategies, using different model scales and data published by NETA. Results show that evolutionary computation enabled game theory involved modelling and decision making provides an effective tool for NETA trading analysis, prediction and support

    Critical behaviours of contact near phase transitions

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    A central quantity of importance for ultracold atoms is contact, which measures two-body correlations at short distances in dilute systems. It appears in universal relations among thermodynamic quantities, such as large momentum tails, energy, and dynamic structure factors, through the renowned Tan relations. However, a conceptual question remains open as to whether or not contact can signify phase transitions that are insensitive to short-range physics. Here we show that, near a continuous classical or quantum phase transition, contact exhibits a variety of critical behaviors, including scaling laws and critical exponents that are uniquely determined by the universality class of the phase transition and a constant contact per particle. We also use a prototypical exactly solvable model to demonstrate these critical behaviors in one-dimensional strongly interacting fermions. Our work establishes an intrinsic connection between the universality of dilute many-body systems and universal critical phenomena near a phase transition.Comment: Final version published in Nat. Commun. 5:5140 doi: 10.1038/ncomms6140 (2014

    Business integration models in the context of web services.

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    E-commerce development and applications have been bringing the Internet to business and marketing and reforming our current business styles and processes. The rapid development of the Web, in particular, the introduction of the semantic web and web service technologies, enables business processes, modeling and management to enter an entirely new stage. Traditional web based business data and transactions can now be analyzed, extracted and modeled to discover new business rules and to form new business strategies, let alone mining the business data in order to classify customers or products. In this paper, we investigate and analyze the business integration models in the context of web services using a micro-payment system because a micro-payment system is considered to be a service intensive activity, where many payment tasks involve different forms of services, such as payment method selection for buyers, security support software, product price comparison, etc. We will use the micro-payment case to discuss and illustrate how the web services approaches support and transform the business process and integration model.

    Adsorption/desorption and electrically controlled flipping of ammonia molecules on graphene

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    In this paper, we evaluate of the adsorption/ desorption of ammonia molecules on a graphene surface by studying the Fermi level shift. Based on a physically plausible model, the adsorption and desorption rates of ammonia molecules on graphene have been extracted from the measured Fermi level shift as a function of exposure time. An electric field-induced flipping behavior of ammonia molecules on graphene is suggested, based on field effect transistor (FET) measurements
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