السلام عليكم
في كتاب Algorithms i a Nutshell
في الجزء الخاص بشرح n log n
لم افهم هذا الجزء
If we expand this out once more, we see that: t(n)=2*[2*[2*t(n/8)+O(n/4)]+O(n/2)]+O(n) This last equation reduces to t(n)=8*t(n/8)+O(3*n). In general, then, we can say that t(n)=2k*t(n/2k)+O(k*n). This expansion ends when 2k=n, that is, when k=log(n). In the final base case when the problem size is 1, the performance t(1) is a constant c. Thus we can see that the closed-form formula for t(n)=n*c+O(n*log(n)). Since n*log(n) is asymptotically greater than c*n for any fixed constant c, t(n) can be simply written as O(n log n).
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t(n)=n*c+O(n*log(n))
ولماذا فرض هذا
Since n*log(n) is asymptotically greater than c*n for any fixed constant c, t(n) can be simply written as O(n log n).
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