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Standard neural network model is the interconnection of a linear dynamic system and a bounded static nonlinear operator, which is depicted as a linear differential inclusion to be analyzed easily with linear matrix inequalities technique.

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We first show some properties of such operators and give an explit description about the image of a linear bounded operator on a linear normed space. Then based on these results, we show the mean ergordic theorem on a C*-bial-gebra and get a sufficient and necessary condition for a linear functional to be Haar measure. Finally we discuss the sufficent conditions for the existence of Haar measure on C*-bialgebras.

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The content of this course is divided into four chapter, the normed linear space and bounded linear operator on the normed space; the character of finite dimensional linear space; the basic theorems on Banach space.

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Linear space and linear transformation, as well as the associated matrix theory, linear algebra is a central element.

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Linear motor is a kind of equipment for converting electrical energy into linear movement use. In most occasions where need converting rotary movement into linear movement, linear motor shows its superiority. It makes many in-between transferring machine unnecessary. Therefore, the whole system runs more steadily. In addition, thanks to the reducing of the in-between machine, the friction wastage of the whole system is reduced and the efficiency of the whole system is improved.

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To overcome the drawback that the traditional Linear Grouping Algorithm, when extracting linear structures, is sensitive to outliers in datasets, a new finite step according to existence of optimal linear grouping in data set and a new algorithm based on k-means clustering, total least absolute deviation and resampling were proposed, which detected several different linear relations at once to minimize the total orthogonal distances from n given points to its nearest hyperplanes.

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