Previously we’ve seen how to use the \{1, x, x^2, \dots x^n\}
If this sounds familiar to you, it’s because this method works very similarly to error-diffusion. Instead of letting adjacent pixels compensate for the error, we’re letting each successive candidate compensate for the combined error of all previous candidates.
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Валерия заступилась за Славу после скандального концертаПевица Валерия заявила, что в скандале на концерте Славы виноваты охранники