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This paper investigates the problem of stabilizing a class of time-varying nonlinear sampled-data systems whose parameters do not change sharply with time. Given this type of sampled-data systems, we make use of the approximate model of the time-varying system at each sampling instant in designing a controller, which can stabilize the exact discrete-time model of the plant under any sufficiently small...
This paper addresses the problem of video scene classification based on the small amount of natural language description created for the video stream. The approach incorporates a conventional tf·idf term-document matrix with scene class specific information derived using the maximum a posteriori (MAP) estimates and the chi-square statistic. Further latent semantic analysis (LSA) is applied to find...
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