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The N-closest or N-best dithering algorithm is a straightforward solution to the N-candidate problem. As the name suggests, the set of candidates is given by the closest palette colours to the input pixel. To determine their weights, we simply take the inverse of the distance to the input pixel. This is essentially the inverse distance weighting (IDW) method for multivariate interpolation, also known as Shepard’s method. The following pseudocode sketches out a possible implementation:

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第二十五条 一般纳税人取得的固定资产、无形资产或者不动产(以下统称长期资产),既用于一般计税方法计税项目,又用于简易计税方法计税项目、免征增值税项目、不得抵扣非应税交易、集体福利或者个人消费(以下统称五类不允许抵扣项目)的,属于用作混合用途的长期资产,对应的进项税额依照增值税法和下列规定处理:

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