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于 2009-06-17 发布文件大小:1KB

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运用MATLAB编程实现计算两序列x1(n)={1,2,3,4,5},x2(n)={1,2,3,4,5,4,3,2,1}的圆周卷积(Calculated using MATLAB programming to achieve the two sequences x1 (n) = (1,2,3,4,5), x2 (n) = (1,2,3,4,5,4,3,2,1) of circular convolution)

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In machine learning, support vector machines (SVMs, also support vector networks[1]) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that assigns new examples into one category or the other, making it a non-probabilistic binary linear classifier. An SVM model is a representation of the examples as points in space, mapped so that the examples of the separate categories are divided by a clear gap that is as wide as possible. New examples are then mapped into that same space and predicted to belong to a category based on which side of the gap they fall on.

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MATLAB

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