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The problem of minimizing roundoff noise and pole sensitivity simultaneously subject to l2-norm scaling constraints of dynamic range for 2-D digital filters with separable denominator is investigated. A novel measure for the evaluation of roundoff noise and pole sensitivity is introduced and then an effective method for minimizing the measure is explored by converting the constrained optimization...
This paper presents a novel algorithm for efficiently minimizing the nuclear norm of a matrix subject to structural and semi-definite constraints. It requires performing only thresholding and eigenvalue decomposition steps and converges Q-superlinearly to the optimum. Thus, this algorithm offers substantial advantages, both in terms of memory requirements and computational time over conventional semi-definite...
During IC photomask vision inspection, considering problem that fine image defectpsilas fineness, complex shape, extraction feature difficultly, and effect by noise easily, presented defect identification classification algorithm based on PCA (principal components analysis) and SVM (support vector machine). It resolved the problem that fine and complex defect was difficult to classify, by merits of...
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