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Question: In this problem, when the base of a logarithm is left unspecified, it is taken to be base-2. So, log n means log2 n.
(a) Recall the Little Master Theorem (LMT). It was shown there, using the iteration method, that T(n) = Θ(n log_b a ) if a > b. Use a similar approach to establish that T(n) = Θ(n log n) if a = b and T(n) = Θ(n) if a < b. Assume that n = b^k for some k ≥ 0, (Note that a Θ(·) bound is sought here, not O(·).)
(b) Use the Master Theorem (MT) to solve the following recurrence: T(1) = Θ(1) and, for n > 1, T(n) = 2T(n/4) + n log n. Be sure to identify clearly which case of the MT applies.
(c) Use the Master Theorem (MT) to solve the following recurrence: T(1) = Θ(1) and, for n > 1, T(n) = 2T(n^(1/4) ) + 1. Be sure to identify clearly which case of the MT applies.
Compute the covariance in several ways. One basic way to derive it is the following. Consider the standard normally distributed random vector
1. consider the following code fragment for the mips five stage pipelined processorinstruction1 add 1 8 3 1 8
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