Data Structures &amp; Alogs HW_Part_4

# Data Structures &amp; Alogs HW_Part_4 - 13 iii...

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13 iii. Induction Step. Consider the case where n + 1 pigeons are in n holes. Eliminate one hole at random. If it contains one pigeon, eliminate it as well, and by the induction hypothesis some other hole must contain at least two pigeons. If it contains no pigeons, then again by the induction hypothesis some other hole must con- tain at least two pigeons (with an extra pigeon yet to be placed). If it contains more than one pigeon, then it fi ts the requirements of the theorem directly. 2.26 (a) When we add the n th line, we create n new regions. But, we start with one region even when there are no lines. Thus, the recurrence is F ( n ) = F ( n 1) + n + 1 . (b) This is equivalent to the summation F ( n ) = 1 + i =1 ni . (c) This is close to a summation we already know (equation 2.1). 2.27 Base case : T ( n 1) = 1 = 1(1 + 1) / 2 . Induction hypothesis : T ( n 1) = ( n 1)( n ) / 2 . Induction step : T ( n ) = T ( n 1) + n = ( n 1)( n ) / 2 + n = n ( n + 1) / 2 . Thus, the theorem is proved by mathematical induction. 2.28 If we expand the recurrence, we get T ( n ) = 2 T ( n 1) + 1 = 2(2 T ( n 2) + 1) + 1) = 4 T ( n 2 + 2 + 1 . Expanding again yields T ( n ) = 8 T ( n 3) + 4 + 2 + 1 . From this, we can deduce a pattern and hypothesize that the recurrence is equivalent to T ( n ) = n i =0 12 i = 2 n 1 . To prove this formula is in fact the proper closed form solution, we use math- ematical induction. Base case : T (1) = 2 1 1 = 1 .

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14 Chap. 2 Mathematical Preliminaries Induction hypothesis : T ( n 1) = 2 n 1 1 . Induction step : T ( n ) = 2 T ( n 1) + 1 = 2(2 n 1 1) + 1 = 2 n 1 . Thus, as proved by mathematical induction, this formula is indeed the correct closed form solution for the recurrence.
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